Novasinergia 2021, 4(1), 6-41. https://doi.org/10.37135/ns.01.07.01 http://novasinergia.unach.edu.ec

Review Article

5G networks: A review from the perspectives of

architecture, business

models, cybersecurity, and

research developments

Redes 5G: una revisión desde las perspectivas de arquitectura, modelos de negocio,

ciberseguridad y desarrollos de investigación

Juan Aranda

1

, Erwin J. Sacoto-Cabrera

2

, Daniel Haro-Mendoza

3

, Fabián Astudillo-Salinas

4

1

Universidad Sergio Arboleda, Bogotá, Colombia,110221

2

Universidad Politécnica Salesiana, Cuenca, Ecuador, 170517; esacoto@ups.edu.ec

3

Facultad de Informática, Universidad Nacional de La Plata, Buenos Aires, Argentina, 1900;

eduardo.harom@info.unlp.edu.ar

4

Universidad de Cuenca, Cuenca, Ecuador, 010107;

fabian.astudillos@ucuenca.edu.ec

*Corresponding: juan.aranda@usa.edu.co

Citación: Aranda, J., Sacoto-

Cabrera, E., Haro-Mendoza,

D., & Astudillo-Salinas, F.,

(2021). 5G networks: A

review from the

perspectives of architecture,

business models,

cybersecurity, and research

developments. Novasinergia.

4(1). 6-41.

https://doi.org/10.37135/ns.

01.07.01

Received: 30 April 2021

Accepted: 26 May 2021

Published: 1 June 2021

Abstract: 5G technology is transforming our critical networks, with long-term

implications. Since 5G is transitioning to a purely

software-based network, potential

improvements will be software updates, like how smartphones are upgraded.

For the

global enterprise, the 5G arrival would be disruptive. Long-awaited solutions to

various flaws in critical networking

systems will arise due to 5G network adoption.

Furthermore, the shortcomings of technology in contributing to business

growth and

success would be turned on their heads. The more complicated part of the actual 5G

race is retooling how we protect

the most critical network of the twenty-first century

and the ecosystem of devices and applications that sprout from that network

due to

cyber software vulnerabilities. The new technologies enabled by new applications

running on 5G networks have much

potential. However, as we move toward a

connected future, equal or more attention should be paid to protecting those links,

computers, and applications. We address critical aspects of 5G standardization and

architecture in this article. We also provide a

detailed summary of 5G network

business models, use cases, and cybersecurity. Furthermore, we perform a study of

computer

simulation methods and testbeds for the research and development of

potential 5G network proposals, which are elements that

are rarely addressed in

current surveys and review articles.

Novasinergia

ISSN: 2631-2654

Keywords: 5G networks, architecture, business models, network security, research

developments.

Copyright: 2021 derechos

otorgados por los autores a

Novasinergia.

Este es un artículo de acceso

abierto distribuido bajo los

términos y condiciones de

una licencia de Creative

Commons Attribution (CC

BY NC).

(http://creativecommons.or

g/licenses/by/4.0/).

Resumen: La tecnología 5G está transformando nuestras redes críticas, con implicaciones a largo

plazo. Dado que 5G está en transición a una red puramente basada en software, las mejoras

potenciales serán las actualizaciones de software, como la forma en que se actualizan los teléfonos

inteligentes en la actualidad. Para la empresa global, la llegada de 5G sería disruptiva. Las

soluciones largamente esperadas para una variedad de fallas en los sistemas clave de networking

surgirán debido a la adopción de la red 5G. Además, las deficiencias de la tecnología en términos

de contribuir al crecimiento empresarial y al éxito se pondrán de cabeza. La parte más complicada

de la carrera 5G real es reestructurar la forma en que protegemos la red más crítica del siglo XXI

y el ecosistema de dispositivos y aplicaciones que surgen de esa red debido a las vulnerabilidades

cibernéticas del software. Las nuevas tecnologías habilitadas por las nuevas aplicaciones que se

ejecutan en redes 5G tienen mucho potencial. Sin embargo, a medida que avanzamos hacia un

futuro conectado, se debe prestar igual o mayor atención a la protección de esos enlaces,

computadoras y aplicaciones. En este artículo se abordan los aspectos clave de la estandarización

y la arquitectura 5G. También se proporciona un resumen detallado de los modelos comerciales de

redes 5G, casos de uso y ciberseguridad. Además, se realiza un estudio de métodos de simulación

por computadora y bancos de pruebas para la investigación y el desarrollo de posibles propuestas

de redes 5G, que son elementos que rara vez se abordan en estudios y artículos de revisión actuales.

Palabras claves Arquitectura, desarrollos de investigación, modelos de negocio, redes 5G,

seguridad de red,

Novasinergia 2021, 4(1), 6-41 7

1. Introduction

The popularization of mobile and smart devices and the innovation of technologies has

introduced applications and services

with requirements such as high performance, security, quality

of service (QoS), and mobility. These requirements have

driven the evolution of wireless

communication technologies. 5G networks are expected to meet the needs of a wide range of

applications, with different demands and in diverse and heterogeneous scenarios.

Designing a network capable of delivering these services with a single, predefined set of essential

network functions would be

highly complex and expensive. Faced with this situation, there is a

certain consensus that 5G networks will be characterized by

having a dense, heterogeneous, and

shared network infrastructure between different operators, transparent use of multiple access

technologies (LTE-A, millimeter wave (mmWave), WiFi, among others), the softwarization and

virtualization of communication

functions and protocols.

5G has a vision-oriented to services consolidated in the scientific and technical community. A

proposal aimed at facilitating

the 5G vision is implementing the concepts of network

softwarization, network virtualization, and network slicing

(NS). Implementing these concepts

allows the execution of new and diverse use cases and business models. The International

Telecommunication Union’s (ITU) 5G vision outlines use cases with a wide range of technological

efficiency and system

specifications, necessitating the interconnection of mobile networks with

non-3GPP network technologies. A single network

provider in their domain would not be able to

do this. There is a clear need for network-to-network interoperability that is also

stable and reliable.

Although the 3GPP has released 5G specifications that describe inter-network communications

interfaces,

further work is needed to improve interface functionality, performance, and security.

Effective partnerships are required between

various network operators and equipment owners, such

as transportation companies, rural and local communities and authorities,

and publicly funded

organizations to achieve seamless interoperability. Network boundaries must be protected across all

borders

to achieve end-to-end reliability.

The complexity of the new systems is increased by the interconnection of 3GPP and non-3GPP

networks, new 5G use cases

with varying specifications, new 5G innovations, and evolutionary

approaches throughout the mobile network. This introduces

new protection vulnerabilities and a

substantially wider attack surface, necessitating a detailed assessment of the threats and

vulnerabilities and identifying work items to mitigate them. Furthermore, the complexities of

implementing

stable 5G networks while meeting the needs of multiple 5G use cases create a trade-

off between network efficiency and security.

Traditional protection approaches would be ineffective due to increased network-to-network

complexity, end-to-end cross-layer

device security, and sensitive applications.

A review of the essential aspects of the architecture, business models, and network security of

5G is

conducted. A reference work is presented to serve as an overview for researchers and

stakeholders in 5G. The particular aspect

of this study is that it provides the main simulation tools,

key performance indicators (KPIs), and testbeds to evaluate future

5G innovations and proposals’

performance.

1.1. Literature Review of Existing 5G Surveys

Several survey and review articles in the literature consider different perspectives of 5G

networks. Next, a

synthesis of relevant existing surveys and reviews related to 5G enabling

Novasinergia 2021, 4(1), 6-41 8

technologies (Yachika, Kaur, & Garg, 2021) such

as mmWave, massive multiple-input multiple-

output (MIMO), beamforming, non-orthogonal multiple access (NOMA), and

NS is presented.

Also, surveys on relevant aspects related to security and privacy and network coexistence

are

revised. Finally, surveys regarding the integration of 5G and some emerging technologies such as

the Internet of Things

(IoT), blockchain, machine learning, deep learning, and reinforcement

learning are also considered. Table 1 presents a summary

of the key aspects explored and the main

challenges discussed in selected references.

The references were selected after conducting a systematic literature review using Scopus as the

main search motor with

the search query defined as follows: TITLE-ABS-KEY(5G AND (Wireless

OR (Mobile communication) OR Technology) AND

((literature Review) OR Survey). Google Scholar was

also used as a secondary search motor using similar words for the search

query. Finally, to ensure

the quality of the papers, the following criteria were considered in the reviewing process:

documents

published in peer-reviewed journals and conference papers during the last five years

and in English.

The remainder of this paper covers important aspects of 5G standardization and architecture (Section

II) and a comprehensive

overview of use cases and business models (Section III) and cybersecurity

in 5G networks (Section IV). Furthermore, a review

of computer simulation tools and testbed for

research and development of future proposals for 5G networks is provided

(Section V), an aspect

that is lacking review in existing surveys. Finally, Section VI draws the conclusions.

Table 1:

Relevant surveys and review of 5G enabling technologies and key aspects

.

Reference

Key aspects explored

Key open challenges

(Khan, Naseem, Siraj,

Razzak, & Imran,

2020)

Describe existing mmWave path loss models.

The role of unmanned aerial vehicle (UAV) as

a relay base station in 5G networks (backhaul

or access communication links) using

mmWave is discussed.

Performance evaluation of the link UAV-gNB

using mmWave at the backhaul and access

link and its integration with the existing

heterogeneous networks (e.g., 3G/LTE

(Chataut & Akl, 2020)

An extensive overview of massive MIMO

systems (benefits, importance, challenges)

Massive MIMO system deployment and test:

pilot contamination, channel estimation,

precoding, user scheduling, hardware

impairments, energy efficiency, and signal

detection.

(Mohamed, Alias,

Roslee, & Raji, 2021)

Describe the fundamentals of beamforming

technology and how it can be implemented.

Identification of interference when

interferers move to eliminate interference in

switched, scanning, and sectored

beamforming types.

(Akbar, Jangsher, &

Bhatti, 2021)

(Mathur & Deepa,

2021)

Review of the basic principles of NOMA and

in-depth analysis of different NOMA

schemes. Recent developments in NOMA

are reviewed.

Design of spreading sequences or

codebooks. Analysis of heterogeneous

collaborative communication schemes with

NOMA. Consideration of imperfect channel

state information (CSI) and sidelink control

information (SCI) in theoretical analysis of

NOMA. Analysis of NOMA in mmWave

Communication and visible light

communication (VLC).

(Khan, Kumar, Jayakody,

& Liyanage, 2020)

(Sanenga, y otros,

2020)

An in-depth review on security and privacy

issues in key network softwarization

technologies (NFV, SDN, MEC, NS).

Examine security monitoring and

management in 5G networks. Overview on

5G standardization security forces. A

comprehensive review of physical layer

security (PLS) based on optimization

techniques.

A secure landscape is needed for 5G

enabling technologies where existing and

new types of attacks are considered.

Breakthrough techniques are required for

access control (security, access rights, and

access revocations), SDN (deep security

schemes), MEC (treat vectors and

vulnerability identification), NFV (e.g.,

service insertion, multi-domain policy), NS

(security mechanisms). Security

standardization for 5G. Cryptography

design and implementation of an optimal

secure transmit precoding algorithm for PLS

Novasinergia 2021, 4(1), 6-41 9

Table 1: Continuation

.

Reference

Key aspects explored

Key open challenges

(Agiwal, Kwon,

Park, & Jin, 2021)

(Mamadou,

Toussaint, &

Chalhoub, 2020)

(Xu, Gui, Gacanin, &

Adachi, 2021)

Review of 4G-5G dual connectivity in detail.

Evaluate the performance of 4G-5G inter

working. Analysis of coexistence techniques

for spectrum sharing (resource sharing and

mutualization) between 5G and access

solutions in unlicensed frequency bands. A

comprehensive review on resource

allocation algorithms (RAAs) in

heterogeneous networks (HetNets).

Conduct a performance evaluation of LTE

and NR. A study of frequency usage

efficiency of 4G-5G dual connectivity is

needed. Proposal of mechanisms and

standardization to improve resource

efficiency and to allow fairness of spectrum

sharing and QoS guarantees in access in

coexistence scenarios. Design of intelligent-

based RAAs for HetNets.

(Nguyen, Pathirana,

Ding, & Seneviratne,

2020)

(Santos, Endo,

Sadok, & Kelner,

2020)

(Fourati, Maaloul, &

Chaari, 2021)

(Xiong, et al., 2019)

(Chettri & Bera,

2020)

A comprehensive review on the integration

of blockchain with 5G technologies and

services. The scope of machine learning,

deep learning, and reinforcement learning

models applied to 5G networks for

processing monitoring data and automating

decisions, intrusion and anomaly detection,

mobile edge caching, cell fault

management, interference mitigation, and

handover problem. An in-depth review on

the integration of the Internet of Things in

5G networks.

Develop of optimized blockchain platforms

for meeting low latency requirements and

smart contracts in-network softwarization

technologies. Need of standardization and

regulations, and infrastructure in existing

5G networks for blockchain integration.

Optimization of networks and architecture

to provide massive connectivity of IoT

devices is required.

Develop simpler, compressed, and agile

deep learning and reinforcement learning

models to attend to the needs of 5G

networks in real-time.

2. 5G standardization and architecture overview

The third-generation partnership project (3GPP) brings together seven

telecommunications standard development organizations (ARIB, ATIS, CCSA, ETSI, TSDSI, TTA,

and TTC), known as organizational partners, that create reports and specifications

that determine

3GPP technologies. The project includes cellular telecommunications technology, such as radio

access, core

network, and service capabilities, and provides a comprehensive overview of mobile

telecommunications systems. Non-radio

links to the core network and interworking with non-

3GPP networks are also covered by these 3GPP specifications. Member

companies, working

groups, and the technical specification community (TSG) all contribute to 3GPP specifications and

studies.

These groups’ 3GPP technologies are continuously developing across successive

generations ("G’s") of commercial cellular and

mobile systems. 3GPP has been the focal point for

most mobile systems beyond 3G, with LTE, LTE-Advanced, LTE-Advanced

Pro, and 5G work

(3GPP, 2021).

Even though these generations have become an appropriate descriptor for the type of network

under consideration,

real progress on 3GPP standards is determined by the milestones reached

in specific releases. When a release is over, new

features are functionally frozen and ready to be

implemented. 3GPP operates on several releases simultaneously, beginning

future development

well ahead of the current release’s completion. While this adds a layer of uncertainty to the groups’

work,

it ensures that progress is steady and consistent.

Figure 1 illustrates the timeline for the most recent and near-time-future 3GPP releases. The

3GPP TSG radio access

network (TSG RAN) is responsible for defining the functions,

requirements, and involving radio performance, physical layer,

and definitions of the operation

and maintenance requirements of conformance testing for user equipment and base stations.

Novasinergia 2021, 4(1), 6-41 10

Figure 1: 5G Timeline (3GPP, 2021)

Release 15, finalized in June 2018, included the first version of the 5G/New Radio (NR) technology

and a set of new features as part of

the LTE evolution. Release 16 includes several significant

enhancements and extensions to NR as part of the first step in the

NR evolution, together with

additional LTE extensions and enhancements. Release-16 finalization was targeted for June 2020,

with the physical layer specifications already finalized in December of 2020. Release 17 will be the

main 3GPP activity during

2020 and 2021, with target finalization in September 2021. The decisions

on a set of study/work items for 3GPP Release 17

were made in December 2019 to improve network

capacity, latency, coverage, power efficiency, and mobility.

2.1. 5G system architecture

Parallel to 3GPP’s work on NR radio-access technology, the overall system architectures of

both the radio-access network

(RAN) and the core network (CN), including the functionality

split between the two networks, were revisited. The RAN

oversees the overall network’s radio-

related features, such as scheduling, radio-resource management, re-transmission

protocols,

coding, and various multi-antenna schemes.

The 5G core network oversees functions that are not directly related to radio access but are needed

to provide a full

network. This involves things like authentication, billing, and setting up end-

to-end connections. Managing these functions separately, rather than incorporating them into the

RAN, is advantageous since it enables many radio-access technologies to be

supported by the same

core network. When using NR in non-standalone mode, where LTE and EPC handle features like

link

setup and paging, it is possible to connect the NR radio access network to the legacy long-

term evolution (LTE) core network

known as the evolved packet core (EPC). In later releases, the

standalone operation will be introduced. NR connects to the

5G core, and LTE connecting to the

5G core. Unlike the transition from 3G to 4G, where the 4G LTE radio-access technology

cannot

link to a 3G core network, the LTE and NR radio-access schemes and their corresponding core

networks are closely

linked (Dahlman, Parkyall, & Skold, 2020).

2.2. Core Network

The 5G core network improves on the EPC by adding three new features: service-based

architecture,

NS support, and a control-plane/user-plane split. The 5G core is built on a service-

Novasinergia 2021, 4(1), 6-41 11

based architecture. This means that the

specification focuses on the core network’s resources and

functionalities rather than nodes. This is understandable, given that

today’s core network is already

heavily virtualized, with core network functionality running on commodity computer hardware.

The term NS is widely used in the sense of 5G. A network slice is a logical network that serves

a specific

business or customer need by combining the required functions from the service-based

architecture. One network slice, for

example, may be set up to serve mobile broadband

applications with maximum mobility support, close to what LTE offers.

Another slice can be

dedicated to a non-mobile, latency-sensitive industry automation program. These slices will all run

on the

same underlying physical core and radio networks, but from the viewpoint of end-user

applications, they will appear as separate

networks. It is close in several ways to set up several

virtual machines on the same physical machine. Edge computing can

be used in a network slice like

this. A network slice may also include sections of the end-user program that run close to the core

network edge to provide low latency.

The 5G core network architecture emphasizes a control-plane/user-plane split, with separate

bandwidth scaling for the two.

Suppose more control plane capacity is needed, for example. In that

case, it should be simple to add it without affecting the network’s user plane.

On a high level, the

5G core can be illustrated using a service-based representation as depicted in figure 2, with

the

emphasis on the services and functionalities. In the requirements, there is also a reference-point

definition that focuses on

the point-to-point interaction between the functions, but that description

is not captured in figure 2.

Figure 2: 5G service-based representation (Dahlman et al., 2020).

The user-plane function (UPF) and the gateway between the RAN and external networks such

as the Internet make up

the user-plane function. Packet routing and forwarding, packet

verification, QoS management, packet filtering, and traffic

measurements are among its duties.

When required, it also acts as an anchor point for (inter-RAT) mobility. Many components comprise

the control-plane functions, such as the session management function (SMF). IP address allocation

for the system (also known as user equipment, UE), policy compliance control, and general session-

management functions are

all handled by the SMF. The access and mobility management function

(AMF) takes care of control signaling between the core

network and the device, security for user

data, idle-state mobility, and authentication. The functionality operating between the

core network,

specifically the AMF, and the device is sometimes referred to as the non-access stratum (NAS), to

separate it

from the access stratum (AS), which handles functionality operating between the device

and the radio access network. Besides,

the core network can also handle other types of functions,

for example, the policy control function (PCF) responsible for policy rules, the unified data

management (UDM) responsible for authentication credentials and access authorization, the

network

exposure function (NEF), the NR repository function (NRF), the authentication server

function (AUSF) handling authentication

functionality, and the application function (AF).

Novasinergia 2021, 4(1), 6-41 12

It is worth noting that the network’s core functions can be applied in a variety of ways. Many of

the features, for example,

may be implemented on a single physical node, spread across several

nodes, or run on a cloud platform. The above definition

focuses on the new 5G core network,

which is being implemented concurrently with NR radio access and can handle both NR and

LTE radio accesses. It is also possible to link NR to EPC, the LTE core network, to allow for an

early implementation of NR in existing networks. LTE is used for control-plane features such as

initial access, paging, and

versatility, which is referred to as “non-standalone service.” eNB and

gNB can be thought of as base stations for LTE and NR,

respectively.

2.3. Radio Access Network

The radio access network can have two types of nodes connected to the 5G core network:

•

A gNB, serving NR devices using the NR user-plane and control-plane protocols; or

•

An ng-eNB, serving LTE devices using the LTE user-plane and control-plane protocols.

An NG-RAN is a radio access network that includes both ng-eNBs for LTE and gNBs for NR

radio access. However, RAN

will be used in the following for simplicity. Furthermore, since the

RAN would be related to the 5G core, 5G

terms such as gNB will be used. To put it another way,

the definition will be based on a 5G core network and an NR-based

RAN. However, as previously

mentioned, the first version of NR is linked to the EPC and operates in a non-standalone mode.

Although the naming of the nodes and interfaces varies slightly, the concepts are similar in this

case.

The gNB (or ng-eNB) is

responsible for all radio-related functions in one or several cells, for

example, radio resource management, admission control,

connection establishment, routing of

user-plane data to the UPF, and control-plane information to the AMF, and QoS flow

management.

It is necessary to remember that a logical node, not a physical implementation, is what a gNB is.

A three-sector site is a

standard implementation of a gNB, in which a base station handles

transmissions in three cells, but other configurations exist,

such as a single baseband processing

unit to which multiple remote radio heads are attached. Many indoor cells or several

cells along

a highway belonging to the same gNB are examples. Therefore, a base station is a potential

implementation of a

gNB, although it is not the same. As can be seen in figure 3, the gNB is

connected to the 5G core network utilizing the NG

interface, more specifically to the UPF through

the NG user-plane part (NG-u) and to the AMF through the NG control-plane

part (NG-c). One

gNB can be connected to multiple UPFs/AMFs for load sharing and redundancy. The Xn interface

connecting

gNBs is mainly used to support active-mode mobility and dual connectivity. This

interface may also be used for multicell radio

resource management (RRM) functions. The Xn

interface is also used to support lossless mobility between neighboring cells

through packet

forwarding.

The F1 interface can also be used to break the gNB into two components, a central unit (gNB-

CU) and one or more

distributed units (gNB-DU). The RRC, PDCP, and SDAP protocols, which

are defined in more detail below, are located in

the gNB-CU, while the remaining protocol entities

(RLC, MAC, and PHY) are located in the gNB-DU in the case of a split

gNB. The Uu interface is

the link between the gNB (or gNB-DU) and the device. At least one connection between the device

and the network is necessary for a device to communicate. The system is initially connected to

a single cell that handles

both uplink and downlink transmissions. This cell is in control of all

data flows, user data, and RRC signaling. This is a

reliable and straightforward solution that can

Novasinergia 2021, 4(1), 6-41 13

be used in a variety of situations. Allowing the system to bind to the network via several cells, on

the other hand, may be advantageous in certain situations. User-plane aggregation is one example

in which

data flows from several cells are combined to maximize the data rate. Another example

is control-plane/user-plane separation,

in which one node handles control plane communication,

and another handles user plane communication. Dual connectivity

refers to a situation in which

a computer is connected to two cells. Dual connectivity between LTE and NR is especially

important because it is the foundation for non-standalone service. The LTE-based master cell

oversees control-plane

and (potentially) user-plane signaling, while the NR-based secondary cell

oversees only user-plane signaling, effectively

boosting data speeds. Dual connectivity between

NR and NR is not part of the December 2017 version of release 15 but was

possible in the final

July 2018 version of release 15.

Figure 3: 5G network implementation (Dahlman et al., 2020).

3. Business models & applications (use cases & KPIs; private 5G and 5G

IoT)

5G leverages the option to build virtual corporate networks within the network itself, a

function known as NS (Foukas, Patounas, Elmokashfi, & Marina, 2017; Afolabi, Taleb, Samdanis,

Kasentini, & Flinck, 2018). Each of these slices is created

with guaranteed service quality

parameters and customized according to the specific needs of each company or organization

(Kaloxylos, 2018). Their customization, i.e., their creation as private networks, ensures a good

quality of service, increasing

their reliability (Su et al., 2019). Any facility will have its own 5G

node, which will provide a specific network

segment adapted to its particularities and QoS

(Laghrissi & Taleb, 2018).

We can attribute this adaptive network model to two technologies: network virtualization and edge

computing.

The former is the result of the combination of two technologies: NFV enables

applications to be deployed on one or more

virtual machines, while SDN centralizes the

management of these distributed applications, as described in Section II and the

authors in (Ge,

Zhou, & Li, 2019; Abdelwahab, Hamdaoui, Guizani, & Znati, 2016).

With the development of edge computing, or cloud computing, companies can process data and

apply decision algorithms

close to the IoT devices that generate the information. This fact seems

insignificant, helps alleviate the load on cloud traffic, reduces latency, and speeds data

analysis in real-time (Hassan, Yau, & Wu, 2019; Hu, Patel, Sabella , Sprecher, & Young, 2015). This

new approach to transmitting information opens up new possibilities across the board, especially

compared to the long distances that data has to travel today with the need to send it to processing

environments.

Novasinergia 2021, 4(1), 6-41 14

Several papers (Afolabi et al., 2018; Kazmi, Khan, Tran, & Hong, 2019) discuss in detail NS, which

enables

the sharing of a common physical infrastructure for different network services (Foukas et

al., 2017). Physical infrastructure

includes wireless access networks, cloud computing servers, Wi-

Fi access points, to name a few. The following is carried out

an analysis of the most relevant

elements of the NS taxonomy based on the literature reviewed, considering the key elements

of

NS architecture, design, technologies, and requirements with a focus on the development of various

possible business models

that can be developed in 5G networks.

•

NS architecture: Several papers (Afolabi et al., 2018; Foukas et al., 2017; Kaloxylos, 2018;

Barakabitze, Ahmad, Mijumbi, & Hines, 2020) describe the NS architecture, which is composed

of infrastructure, network function and service layers (Next Generation Mobile Network

(NGMN) Alliance, 2016). Depending on the layer, NS isolation can be done in many ways:

software-based isolation, physical

isolation, and virtual machine-based isolation

(Kostopoulos, Chochliouros, & Spada, 2019). For this purpose, the Next

Generation Mobile

Networks (NGMN) Alliance (2015), establishes for each network layer the following instances:

5G

service instance layer (5GSIL), 5G network instances layer (5GNSI), 5G physical resource

layer (5GRL). The 5GSIL

represents different services to be supported by the operator (e.g.,

services to mobile virtual network operators (MVNOs)

or end-users), where each service is

created by an instance (Hicham, Abghour, & Ouzzif, 2018). The 5GNSI is a set

of logical

networks that fulfill a service layer instance's required functions and characteristics. A 5GNSI

instance

can also be shared between multiple service instances provided by the network

operator (Hicham et al., 2018). 5GRL

represents the bottom layer of the architecture and

consists of physical and logical resources dedicated to a

network function(s) determined by

the upper layer(s).

•

NS basic design principles: The NS architecture is based on three principles: isolation, elasticity,

and E2E optimization (Afolabi et al., 2018; Foukas et al., 2017; Kaloxylos, 2018).

–

Isolation: is a NS feature that can separate and impose limits on network resource uses;

this feature is

supported by network virtualization (Michalopoulos et al., 2017). It also ensures

the performance of different users

(MVNOs, vertical industries) through an equitable

distribution of resources. Isolation can be deployed (i) by using a

different physical resource,

(ii) when separating via virtualization means a shared resource, and (iii) through sharing

a

resource with the guidance of a respective policy that defines the access rights for each tenant.

–

Elasticity: is an essential operation related to the resource allocated to a particular

network slice. Specifically,

elasticity allows the dynamic management of resources allocated

to network segments according to different users' demands to use them efficiently. Fixed

availability of resources on a network segment can lead to under-, and

over-utilization of

resources due to user demands variations (Li et al., 2017; Kazmi et al., 2019; Abdulghaffar,

Mahmoud, Abu-Amara, & Sheltami, 2021). Therefore, NS is designed with an elastic nature

to simultaneously

satisfy the users QoS and optimize the overall network overhead. The

main challenge in the elasticity application is

the negotiation policy between network

segments so that the performance of the network segments is not affected by

an increase in

the number of users or an increase in QoS. However, this process requires an inter-slice

negotiation

since it may influence the performance of other slices that share the same

resources.

–

Customization E2E: NS's inherent property for facilitating a service delivery from the

service providers to

the end-user(s)/customer(s). Network segments ensure that the network

operator’s shared resources are efficiently

utilized between different users. Network

Novasinergia 2021, 4(1), 6-41 15

segments customization in NS is performed at all layers of the network

topology using the

technical features provided by SDN and supported by the advantages of NFV. As described

by Li et al., (2017); Lin, Tseng, & Wang (2021), E2E a property has two extensions: (i) a slice

that combines resources

that belong to distinct infrastructure providers, (ii) it unifies various

network layers and heterogeneous technologies,

•

Technologies enabling NS: the key virtualization technologies for NS are listed below:

–

SDN: It provides key characters such as flexibility, service-oriented robustness adaptation

and scalability. SDN creates

a virtualized control plane that enables intelligent management

between network functions, eliminating the gap between

service provisioning and network

management, i.e., with SDN network control becomes directly programmable using

standardized interfaces (Afolabi et al., 2018; Ho, Tran, Kazmi, Han, & Hong, 2018; Prabakaran,

Nizar, & Kumar, 2021). The SDN controller manages network slices applying rules when

necessary

and following the corresponding network policy. Furthermore, SDN permits

flexibility into control and data planes

in 5G networks.

–

VNF: It allows the deployment of originally based in hardware network functions (NF)

on virtual environments

leveraging benefits of cloud computing (Afolabi et al., 2018; Ho et

al., 2018; Prabakaran et al., 2021; Nguyen, Brunstrom, Grinnemo, & Taheri, 2017). With NFV,

NFs can be easily deployed and dynamically allocated, as well as

NFs can be assigned to

service providers (SPs) so that mobile network operators (MNOs) can share their infrastructure

(Nguyen et al., 2017; Stallings, 2015; Costa-Perez et al., 2017).

–

Edge computing: technologies as cloud and edge computing offer computational, storage,

and networking facilities

within single or multiple platforms for enabling a network slice

(Hassan et al., 2019; Selvi & Thamiselvan, 2021).

Specifically, edge computing enables data

acquisition and provides services close to end-users allowing a form of

edge-centric

networking, which facilitates data proximity, assuring ultra-low latency, high data rates, and

intelligence

and control. In this regard, multi-access edge computing (MEC) (Rayani, Glitho,

& Elbiaze, 2020; Giust , Costa-Perez, & Reznik, 2017; Giust et al., 2018) system facilitates

information technology (IT) cloud capability at the edge of

the network, and its access-

agnostic characteristics guarantee smoother deployment independent of the underlying

communication network. Besides, mobile edge fog computing (MEFC) is a MEC technology

that provides cloud-computing capabilities with proximity to mobile subscribers, it offers a

service environment with ultra-low latency

and high bandwidth as well as direct access to

real-time radio network information that can be used by applications and services to offer

context-related services.

–

NS based on resources: the segmentation of an operator’s physical network infrastructure

can be done at the different

network levels, from user terminal equipment to core network

equipment, allowing the network segment (MNO,

MVNO, Vertical Industries) manager to

orchestrate and provide services autonomously. In this respect, resources

at the user

terminal level require operators to establish different strategies at the level of each network

segment

concerning QoS. Regarding MNO RAN sharing with MVNOs, different

infrastructure sharing possibilities are studied

by Kazmi, Tran, Ho, & Hong (2017), Ho et al.,

(2018); Zhang, Gui , Tian, & Sun, (2017) w hile modeling the scenarios

as an optimization

problem to satisfy efficient resource allocation needs. In addition to network sharing at the

user

endpoint and RAN level, core network and cloud resources must be efficiently shared

between different network

segments and their users while meeting QoS requirements.

From the above, about segmentation at the different network levels, two scenarios stand out in the

Novasinergia 2021, 4(1), 6-41 16

documents reviewed:

static and dynamic resource allocation for the different network levels

(Kazmi et al., 2017; Ho et al., 2018; Zhang

et al., 2017). Static allocation of a network segment to

an MVNO means that once the resource allocation strategy

across the network segment is

determined, the network segment will have the same capacity regardless of how the

environment

changes (Khan, Yaqoob, Tran, Han, & Hong, 2020). Dynamic allocation of a network segment refers

to

adjusting network resource allocation strategies to optimize the quality of services (Khan et al.,

2020).

In this regard, the ITU has proposed three usage scenarios that can serve as corresponding

standard network slices, with each

targeting different service requirements. These scenarios are

also referred to as slice service types. Within the context of 5G

NS, a slice service type defines the

expected behavior of a network slice in terms of specific features and services. The three

standardized slice service types are:

•

The enhanced mobile broadband (eMBB)

•

The ultra-reliable and low latency communications (URLLC)

•

The massive machine-type communications (mMTC)

As a conclusion of the above, in 5G development are considered that slice allocation means

allocating resources throughout

the network. 5G resources are model as multiple chunks, each one

with a different capacity, spread across the whole physical

network.

Since unforeseen business models and use cases are expected to emerge in the short future, as

detailed above, 5G networks

have the flexibility to support these new requirements.

3.1. Business Models

In the previous generations of mobile networks (2G, 3G), the resources to be assigned to each

application were mainly radio

resources, as described by Sacoto-Cabrera (2021), Camarán & De

Miguel (2008); Varoutas, Katsianis, Sphicopoulos, Stordahl, & Welling (2006). However, 4G

networks development enabled new business models for MVNOs and vertical industries, as

described by Sacoto-Cabrera (2021), Copeland & Crespi (2011), Pousttchi & Hufenbach (2009),

Smura, Kiiski, & Hammainen (2007), and Kim & Park (2004).

Among the business models, it is highlighted:

• Full MVNO: in this model, the resource shared with the MNO is the radio spectrum for

which access charges are set

according to the leased spectrum space. On the other hand, a

Full-MVNO can manage different QoS levels according to

profiles and services that can be

operated within the MVNO platform.

• Multi-MNO: this business model allows an MVNO to connect to multiple MNOs (Multi-

MNOs), considering access to

different services for which MNOs provide different levels of

QoS.

In this respect, several studies introduce different scenarios of network infrastructure sharing

between MNOs and MVNOs in

which their technical and economic feasibility is assessed, as

described by Hultell, Johansson, & Markendahl (2004), Romero & Guijarro (2013), and Guijarro, Pla,

& Tuffin (2013).

Likewise, the development of different business models points to further segmentation of wireless

access networks into

specialized service providers that connect to local service and access

providers, possibly through an infrastructure provider

(InP) that provides services to the different

MVNOs through service level agreements (SLAs).

Novasinergia 2021, 4(1), 6-41 17

Concerning the above, the 5G mobile network opens unprecedented business opportunities to

telco operators by increasing

their market through the NS characteristics.

NS drives the business models behind the 5G ecosystem by providing an effective way to deliver

heterogeneous services of

interest for different verticals customers as MVNOS, virtual private

network operators (PVMNOs) and, over-the-top operators

(OTTs) (Jiang, Condoluci, Mahmoodi, &

Guijarro (n.d.); Gomes, Ahokangas, & Mogaddamerad, 2016; Golzarjannat, Ahokangas,

Matinmikko-Blue, & Yrjola, 2021).

Table 2 describes the main business models proposed by several authors (Li et al., 2017), whose

classification is based

on the one described by the next generation mobile networks (NGMN)

alliance published in the 5G white paper (Next Generation Mobile Networks (NGMN) Alliance,

2015).

Table 2:

Business models

.

Mobile operator role

Business models

Description

Asset provider

Network sharing

XaaS

5G networks can share network infrastructure between

two or more operators based on static or dynamic

policies.

5G networks can offer to and operate for a 3rd party

provider with different network capabilities as

infrastructure, platform, and network as a service (XaaS)

Connectivity

provider

An extensive overview of massive

MIMO systems

(benefits,

importance, challenges)

In this business model, the customer and service

provider are decoupled from the physical

infrastructure. They are offered no configurability,

and a very low level of configurability, respectively.

The connectivity provider business model requires

modular network architecture, having the capability

to

be exposed to the 5G provisioning/configuration

system.

Partner service

provider

Describe the fundamentals of

beamforming

technology and how it

can be implemented.

Identification of interference when interferers move

to

eliminate interference in switched, scanning, and

sectored beamforming types

The main 5G networks business models described in table 2 require redefining the value chain of an

MNO by considering

the main actors and their interactions. Pujol, Elayoubi, Markendahl, &

Salahaldin (2016), and Curwen & Whalley (2021) identify the new elements that are integrated

into the components of an MNO value chain (customers, competitors,

suppliers, complementary

services). PVMNOs is part of the customer value chain component as a connectivity provider that

leases MNO infrastructure to serve its customers; additionally, all those who provide vertical

services or who lease network

capacity to MVNOs are also part of MNOs customers (Next

Generation Mobile Networks (NGMN) Alliance, 2015). In the competitor value chain component,

large

wireless network providers as Google and Microsoft join in as network competitor. In the

supplier value chain component,

companies that manufacture equipment and software for data

centers, virtualization, among others, join in as suppliers to the

MNOs, while content delivery

networks (CDN) are an important element in the provision of an MNO’s service to host content

near the end-users in the MNO’s network. And the in complementary services value chain

component are added content

providers that encourage their users to buy more mobile data

service capacity, including mobile application developers.

In addition to the business models described in table 2, several documents present different

classifications for business

models in 5G, as follows:

3.1.1. Commercialization business models:

• Business-to-business (B2B): 5G network resources are leased to different vertical companies

offering complementary

services such as IoT, video surveillance, etc. In this model, full

Novasinergia 2021, 4(1), 6-41 18

consumer control in this service delivery chain is released

to the companies (Elayoubi et al.,

2017; Barakabitze et al., 2020).

• Business-to-consumer (B2C): the B2C goal is to create value by detecting new demand for

services enriched by digital

platforms, addressing new consumer and business needs (Elayoubi

et al., 2017; Barakabitze et al., 2020).

• Business to business to customer (B2B2C): new markets and consumer-oriented customers can

partner with 5G network

providers; thus, MNOs play the role of a wholesale provider, i.e.,

they must provide customized network resources to a

third party (MVNO, OTT, vertical market

players). They will have a direct relationship with their end-customer (Elayoubi et al., 2017;

Barakabitze et al., 2020).

3.1.2. Lifecycle:

Zhu, Yu, Berry, & Liu (2019) discussed business models based on lifecycle, service target

market and,

different levels at which MNO network segmentation is performed, the classification

being as follows:

• Industrial NS: in this model, the actors have the same requirements for their users to register on

the same network segment,

which abstracts user demands to a high latency network segment

and a low latency network segment.

• Monopolized NS: in this model, an actor (such as MVNO, OTT, PMVNO) pay for a network

segment and uses it to

serve its users or uses it as a private network.

• NS by events: In this model, the MNO implements network segments with a relatively short

lifetime to cover temporary

events (concerts, sports activities, promotions, among others).

3.1.3. Dynamic and static sharing:

These business models encompass the study of static and dynamic network infrastructure

sharing and the relationship between MNOs and MVNOs, mainly to establish the economic

feasibility of these models for the

different market players.

3.1.4. Multi-MNO:

In these models’ business, an MVNO is considered a customer of its host MNO and

competes with

MNOs and other MVNOs to attract customers.

Few works model the economic relationships, which emerge from a multi-MNO business model.

An analysis of pricing in

a mobile market, driven by two MNOs and a new MVNO that leases

resources and competes with the MNOs is discussed

by

Sacoto-Cabrera (2021), Sacoto-Cabrera,

Guijarro, & Maillé (2020), Khalifa, Benhamiche, Simonian, & Bouillon (2018), and Zhu et al.,

(2019).

3.1.5. Multi-Tenancy:

NS facilitates share MNO infrastructures, accelerating network rollouts and offering services

to customers

with reduced costs (Li et al., 2017; Liu, Yang, & Cuthbert, 2021; Kaloxylos, 2018;

Guijarro, Vidal, Pla, & Naldi, 2019). Samdanis, Costa-Perez, & Sciancalepore (2016) define the

following roles for network sharing solutions:

• Infrastructure provider (InP): the MNO is responsible for the physical network deployment and

maintenance, but InP does

have contact directly with end-users.

• MVNO: MVNOs are tenants of existing InP resources.

Novasinergia 2021, 4(1), 6-41 19

• OTT service providers: in this model, the OTTs operate on top of an InP belonging to an MNO

and based on a pre-defined

SLA set of requirements.

• Vertical industries: in this model, vertical industries exploit an MNO or MVNO network

infrastructure as a tenant or

services complementary telecommunication industry.

In this regard, the authors in Han, Tavade, & Schotten (2017), Sacoto-Cabrera, Guijarro, Vidal, &

Pla, (2020), Han, Feng, Ji, & Schotten (2017), and Guijarro, Vidal, Pla, & Naldi (2019) analyze the

multi-tenant model from the economics relationships that emerge in

NS-based resource allocation

within the context of 5G. Specifically, the above works analyze the global profit maximization

problem of a set of independent mobile VNOs that request slices from an MNO and propose

several allocation mechanisms

for solving this system optimization problem.

3.2. Uses Cases

As described above, the 5G architecture is designed to provide support for three different

generic services eMBB, mMTC,

and URLLC. Likewise, 5G services can be provided through

different slices, where a specific slice can handle user requests

of a particular type, and each offers

distinct QoS to their users.

Besides, NS enables value creation for vertical segments, application providers and third parties

that lack physical network

infrastructure, by offering radio, networking, and cloud resources,

allowing a customized network operation and true service

differentiation.

The main objective of 5G is to enable an end-to-end ecosystem, which meets price-QoS

requirements. To this end, several

use cases are envisaged in the development of 5G (Next

Generation Mobile Networks (NGMN) Alliance, 2015; Afolabi et al., 2018; Navarro-Ortiz et al., 2020),

as detailed

in table 3.

Table 3:

Uses case categories

.

Uses

Description

Examples

Broadband access in

dense areas

The objective is to make services available in densely

populated areas (e.g., dense urban centers, events, multi-store

buildings), where thousands of people per square kilometer

(km

2

) congregate.

Pervasive video

HD video/photo sharing in

stadium/open-air gathering

Broadband access

everywhere

This use of 5G allows access to a minimum amount of

bandwidth, at least 50Mbps, to ensure a globally connected

society.

50+ Mbps everywhere

Ultra-low-cost networks

Higher user mobility

Offers broadband service for mobile users in extremely fast-

moving vehicles.

High-speed train

Remote computing

Moving hot spots

3D (three dimensional)

Connectivity

Massive IoT

Supports the access of sensors and actuators to ultra-dense

broadband networks, considering devices that need super-

low cost, long-range and low power consumption.

Smart wearables (clothes)

Sensor networks

Mobile video surveillance

Extreme real-time

communications

This 5G network use ensures ultra-low latency

connectivity.

Tactile Internet

Ultra-reliable

communications

This 5G network use provide ultra-low latency, reliability,

and availability of network connectivity support.

Automated traffic control and

driving eHealth: Extreme life

critical.

Remote object manipulation:

remote surgery Public safety,

Multi- connection

This use 5G network assures network connectivity for users

with different smart devices.

smart-phones, smart-TV,

among others

Figure 4 shows the mapping from the usage scenarios defined by ITU-R and the use case families

proposed by NGMN.

Novasinergia 2021, 4(1), 6-41 20

As can be seen, URLLC consists of extreme real-time communications, lifeline communications,

and ultra-reliable

communications. The mMTC corresponds to the massive IoT. The eMBB usage

scenario consists of broadband access in dense

areas, broadband access everywhere, increased user

mobility, and broadcast-like services.

Figure 4: 5G use cases.

3.3. Key performance indicators (KPIs)

The KPIs are certain quantitative parameters to evaluate network quality. Specifically, in 5G,

the NGMN defined in (Next Generation Mobile Networks (NGMN) Alliance, 2015) system

performance KPIs and user experience KPIs, as shown in tables 4 and 5, respectively.

Table 4: System performance KPIs.

Uses

Connection density

Traffic density

Broadband access in dense areas

200-2500 /km

DL: 750 Gbps / km

2

UL: 125 Gbps / km

2

Indoor ultra-high broadband access

75,000 / km

(75/1000 m office)

DL: 15 Tbps / km

2

(15 Gbps /1000 km

2

)

DL: 15 Tbps / km

2

(15 Gbps /1000 km

2

)

Broadband access in a crowd

150,000 / km

(30.000 / stadium)

DL: 3.75 Tbps / km

2

(DL: 0.75 Tbps / stadium)

UL: 7.5 Tbps / km

2

UL: 7.5 Tbps / km

2

Mobile broadband in vehicles

2000 / km

2

(500 active users per

train x 4 trains, or 1

active user per car x

2000 cars)

DL: 100 Gbps / km

2

(25 Gbps per train, 50 Mbps per car)

UL: 50 Gbps / km

(12.5 Gbps per train, 25 Mbps per car)

Massive low-cost/long-range/low-power

MTC

Up to 200,000 / km

Not critical

Broadband MTC

200-2500 /km

DL: 750 Gbps / km

2

UL: 125 Gbps / km

2

Ultra-low latency

Not critical

Ultra-high reliability & Ultra-low latency

Not critical

Novasinergia 2021, 4(1), 6-41 21

Table 5: User experience KPIs.

Uses

Uses Experienced Data Rate

E3E Latency

Mobility

Broadband access in dense

areas

DL: 300 Mbps

UL: 50 Mbps

10 ms

On demand, 0-100 km/h

Indoor ultra-high broadband

access

DL: 1 Gbps,

UL: 500 Mbps

10 ms

Pedestrian

Broadband access in a crowd

DL: 25 Mbps

UL: 50 Mbps

10 ms

Pedestrian

Mobile broadband in vehicles

DL: 50 Mbps

UL: 25 Mbps

10 ms

On demand, up to 500

km/h

Massive low-cost/long-

range/low-power MTC

Low (typically 1-100 kbps)

Seconds to

hours

On demand: 0-500 km/h

Broadband MTC

DL: 25 Mbps

UL: 50 Mbps

10 ms

0-120 km/h

Ultra-low latency

DL: 50 Mbps

UL: 25 Mbps

<1 ms

Pedestrian

Ultra-high reliability & Ultra-

low latency

DL: From 50 kbps to 10

Mbps

UL: From a few bps to 10

Mbps

1 ms

On demand: 0- 500 km/h

In Next Generation Mobile Networks (NGMN) Alliance (2015), each KPI is defined, and the

evaluation method is introduced. Also, the target value of each KPI is set for different use cases.

Several studies developed by, 5G European validation platform for extensive (5G EVE) (Gupta et

al., 2019), coordinated multi-point (CoMP) (Song, Wang, Chen, & Jiang, 2018), 5G option 3x

reference model (Soós, Ficzere, Varga, & Szalay, 2020), 5G testbed (Soós et al., 2020), 5GENESIS

(Koumaras et al., 2018), analyze the performance of 5G and the KPIs established in its design. The

5G KPIs studies include different use cases of broadband access in dense areas, high user mobility,

massive IoT, tactile Internet, natural disaster, E-Health services, and broadcast services. They have

set out recommendations for improvements in the design and deployment of 5G networks. These

have set out recommendations for improvements in the design and deployment of 5G networks,

especially in the radio coverage and connection speed, but there are no E2E 5G field trials.

4. Cybersecurity in 5G

The new services and applications offered by the connectivity of emerging 5G networks

will introduce new security

requirements to mitigate vulnerabilities and attacks. These new

requirements must be addressed in the deployment of 5G

networks (Housenovic et al., 2018). The

transition to 5G networks according to the 3GPP is divided into two parts: a) Standalone

networks,

where a 5G core (5GC) network is introduced, and b) non-standalone networks, which will take

advantage of the

same protocols of the plane of LTE control and the LTE evolved packet core

(EPC) network (5G Americas, 2020).

4.1. Threats, vulnerabilities, and attacks

4.1.1. 5G Non-standalone:

The operation of the 5G NSA architecture is based on LTE control plane protocols (see

figure 5),

so the initial 5G NSA launches will only offer Mobile Broadband (eMBB) improvements

(Agiwal, Roy, & Saxena, 2016).

Threats and vulnerabilities presented in LTE will also affect the 5G

NSA network. For a proper transition to 5G, the threats

that occur in 4G must be considered.

Novasinergia 2021, 4(1), 6-41 22

Figure 5: Non-standalone architecture.

The main security threats to the 5G NSA network are described below:

• Downgrade attack, forcing a UE LTE connection to connect to 2G or 3G, even though the end-

user can do so with higher

technology.

• Data modification attacks, UMTS, and LTE communications integrity are not protected by any

security method to intercept

the information flow. This could lead to data injection or

modification, such as man in the middle (MitM) (5G Americas, 2018). Mutual authentication

between the mobile device and the base station can prevent a MitM-type attack. The 5G

AKA and EAP-AKA protocols are emerging solution to record connection requests and then

initiate the authentication

process in 5G networks (Basin et al., 2018).

• IMSI Tracking, when IMSI (International Mobile Subscriber Identity) requests are made. The

international mobile sub-

scriber identity (IMSI) is sent unencrypted over the radio, thus

allowing the attacker to find out which SIM card is using

the connected user.

• Base station spoofing “fake” base stations capable of unknowingly tracking and collecting their

personal data.

• LTE roaming, the use of old signaling protocols with SS7 / diameter vulnerabilities in 2G, 3G

/ 4G could expose users

to listening to voice conversations, reading or transmitting messages,

and tracking phones (ITProPortal, 2019).

4.1.2. 5G standalone:

Figure 6 shows the 5G SA architecture. 5G SA will cover all ITU use cases for 5G,

implementing

independent services and specifications through a new 5GC network and new

protocols to mitigate some known LTE

problems (Housenovic et al., 2018).

One of the critical aspects to differentiate 5G SA from 5G NSA and previous versions is improving

privacy through a service-based architecture with techniques such as SDN and NFV (Americas,

2020). Centralized SDN management and virtualization

of NFV functions expose the functional

domains and weaknesses of the 5G network (Americas, 2018). Among the principal

vulnerabilities

and threats that can affect 5G SA infrastructures, the following can be mentioned: Service-based

architecture:

Information transfer in 5G is software-based. This information is sensitive and

confidential; this is added to weak authentication,

lack of encryption, and insecurity in end devices,

increasing the risk of attack on applications.

Novasinergia 2021, 4(1), 6-41 23

Figure 6: Standalone architecture.

4.1.2.1. SDN and NFV:

To support the high levels of performance and flexibility for massive information generation

and management

applications, 5G must implement new paradigms such as SDN and NFV

(González, 2019). However, as with any new

technology, security risks grow as new threats

emerge. Virtualization allows multiple tenants or network users to share the

same physical

infrastructure and network resources. This can create security vulnerabilities related to

confidentiality, integrity,

authenticity, and non-repudiation (Housenovic et al., 2018). SDN logically

uses the concept of a centralized controller. This

concept introduces a single point of failure in the

controller’s infrastructure; it also represents a bottleneck for the entire network

in the case of

saturation attacks. Another threat is control applications. Control applications can interact

maliciously, trying to

gain control over switches and controllers. The use of Internet security

protocol (IPsec) or transport layer security (TLS) is recommended to protect this communication

in an encrypted way (Forescout Technologies, 2017). Another aspect to consider

is that

communication between each plane of the SDN architecture is carried out using specific SDN

protocols or through

virtual interfaces. These interfaces constitute new points of attack for which

each interface must implement an authentication

and authorization method that ensures the

integrity and confidentiality of the communication (5G Americas, 2019).

4.1.2.2. Threats to the EU:

In Forescout Technologies (2017), a study of IoT security is presented. It concludes that each

new device

at the infrastructure represents a security threat or point of attack. Each of the devices

will be exposed and/or vulnerable. The

main threats to which they are exposed are distributed

denial of services (DDoS) attacks and integrity attacks of data stored

on devices. DDoS attacks

will be carried out through massive requests to the server to deny access to network resources. It

is

a priority to think of solutions with solid authentication from the design phase to mitigate

them. Given the nature of 5G, to

achieve fast authentication, SDN themselves are the best tools

with high flexibility and programmability (Agiwal et al., 2016).

Additionally, 3GPP recommends

using IPSec encryption to prevent attacks from the Internet or botnets that could significantly

affect

5G applications.

4.1.2.3. Man-in-the-middle (MitM):

Like 4G, 5G lacks information integrity protection methods in its specifications. Shaik,

Novasinergia 2021, 4(1), 6-41 24

Borgaonkar, Park, & Seifert (2019) reported that information on an unprotected device’s capabilities

is exchanged during

its registration on the 4G and 5G network. A MitM can exploit this

vulnerability. The three classes of attacks that

can occur are: (i) identification attacks, discovering

devices on the network, knowing their characteristics and applications; (ii) bidding down attacks,

capturing the device’s capabilities, and degrading the data speed; and (iii) battery depletion attacks.

User plane integrity protection can be enabled but requires considerable resource consumption,

affecting the user device’s

performance. IP is enabled on control plane messages, but that still leaves

user data traffic vulnerable because the control plane

and the user plane are separate (Americas,

2020).

4.1.2.4. RAN threats (SUPI):

Unlike 4G and its predecessor technologies, in 5G, the IMSI is not transmitted in plain text.

3GPP has

addressed this by eliminating the clear text IMSI by proposing a permanent subscription

identifier (SUPI), which prevents an

attacker from tracking a target affecting subscribers' privacy.

5G systems guarantee the integrity of the information as it

implements MIMO technology with

multiple inputs and output antennas, operating in the mmWave millimeter wave spectrum

with

data and signals.

4.2. 5G design and security considerations

The security features of the 5G architecture have improvements compared to previous

generations.

These features are based

on proven 4G security mechanisms. The enhancements are primarily based

on enhancements to authentication, encryption, and

assurance of availability, integrity, and privacy.

Figure 7 presents a 5G environment with its principal vulnerabilities and the

design considerations

deployed to mitigate them.

Figure 7: Vulnerabilities and security considerations of the 5G design.

Novasinergia 2021, 4(1), 6-41 25

4.2.1. Mobile edge computing (MEC):

MEC technology enables applications with high real-time demands such as driverless

vehicles, augmented reality (AR), robotics, and immersion media. MEC provides cloud computing

capabilities within RAN

close to mobile users (Pham et al., 2020). Table 6 lists the primary security

protections provided by MEC, as well as their

main threats.

Table 6:

Protections and risks of MEC

.

Protections

Risks

Each container performs a dedicated function, and

this makes it easy to detect anomalies.

Open-source code, more interfaces, and APIs introduce

new

threat vectors

Isolation between containers prevents the spread of

viruses.

Shared resources can generate cross-interference.

Network segmentation separates traffic and isolates

resources.

Vulnerabilities in host container-as-a-service (CaaS) and

plat-

form as a service (PaaS) can affect container security.

Resiliency is gained with increased speed and

dynamic threat response.

Dependency upon central orchestration introduces a

new

threat vector

Efficient software update and security patches

High data volume and sessions increase risk from an

attack.

Vulnerability of applications that run as microservices.

4.2.2. Software-based operations:

5G is based on cloud functions and software. 5G service providers will implement in their

infrastructure: Automation, orchestration, and machine learning (5G Americas, 2020). Process

automation with data collection,

machine learning for analysis, and decision making. Gates of

trust are needed to implement an automated system in a 5G

network properly. An audit must be

executed continuously to ensure that the expected results are achieved; threat intelligence

can be

used to detect and mitigate malicious attacks in real-time. The orchestration will help coordinate

the use of different 5G

resources by providing security enhancements for roaming with the

introduction of the security edge protection proxy (SEPP)

in the 5G core.

4.2.3. NFV security:

A fully virtualized 5G network using the ETSI NFV architecture allows operators to deploy

scalable,

elastic, and highly reliable networks, improving network and user security. NFV can

improve the self-protection of 5G

communications and isolate malicious traffic, thus better

solving DoS and DDoS attacks (ITPortal, 2019). However, due to

the configuration errors

presented by the dynamic nature of NFVs, they are vulnerable to typical attacks of virtualization,

such as flooding, hypervisor hijacking, malware injection, cloud attacks, spoofing, and sniffing

(Ordonez-Lucena et al., 2017).

In Americas (2018), it is mentioned that in NFV, there is the facility to

create, delete and move a virtual machine (VM). Thus,

tracking a VM and ensuring the security of a

hypervisor becomes a complex problem. In this context, the main security challenge

is to protect

hypervisors’ confidentiality and privacy, virtual machines, and management modules through an

authentication

and validation mechanism. NFV provides security service as a service (SECaaS).

Security as a service can be applied to any

application and is a strong use case for 5G technology.

For Hussain, Hussain, & Zeadally (2019), NFV not only provides an

optimal exchange of resources

but also allows agreements, service-oriented policies, monitoring mechanisms, and flow control.

Finally, by combining the features of NFV with SDN, flexibility in 5G security management can be

improved, allowing security

functions to be executed in real-time without altering the underlying

hardware configuration.

Novasinergia 2021, 4(1), 6-41 26

4.2.4. SDN security:

SDN creates a single point of risk that compromises the availability of the entire system.

To mitigate

these availability problems and improve resilience to malicious attacks, a reasonable

solution is the use of controller redundancy (Ordonez-Lucena et al., 2017). Likewise, the centralized

architecture of SDN allows the automation of the management of a security incident. Identification,

status verification, and the application of security policies can be scheduled to run

automatically

(Hussain et al., 2019). Automation would reduce configuration errors and problems in the

application of policies

in the network. Automation enables the deployment of security policies

globally across the entire network, while security services can be deployed on specific traffic

types. SDN embedded programmability allows most network functions to be

implemented as

applications. If malicious applications gain access or critical application programming interfaces

(APIs) are

exposed to malicious software, chaos can spread across the network (Ahmad et al., 2017).

To address the API security issue, data

must be protected end-to-end. This includes the security of

a request from origin to destination, passing through intermediate

elements. API security can

include a) data security on the shipment (between control plane, user plane, and services), and b)

access control and security against DoS. Key sharing can be exploited by network elements using

an encryption algorithm,

validated, and authenticated by a central node. Only the elements

authenticated by the central node will be able to exchange

information (5G Americas, 2020).

4.2.5. Network slicing (NS):

5G network slices are logically isolated, and autonomous networks are flexible and

programmable

enough to accommodate multiple use cases simultaneously over the same network

infrastructure. As mentioned by Ordonez-Lucena, et al. (2017), each slice is autonomous and

independent, thanks to this isolation. Any attack or security problem that

occurs in one slice does

not affect the rest of the slices. Each slice will have its resource and security requirements. A slice

should implement security policies according to the requirements without influencing the rest of

the slices. According to those

mentioned above, the main problem that NS presents is the

possibility of inadequate isolation. The isolation problem can

occur between different slices (inter-

slices) and between the same slice components (intra-slice). This drawback results in a

threat of

being able to migrate across multiple slices. The impact of an attack can be reduced by

implementing adequate

intra-slice isolation, for example, HAND isolation, security domain, VNF

isolation, among others. The desired isolation levels

must accommodate technologies that include

various software, hardware, and cryptography mechanisms (Americas, 2019). In

addition to

isolation, the authors in (Americas, 2020) talks about providing an additional security level to each

slice. A customer

can define the implementation of security policies according to their

requirements and use case. A customer can incorporate

SECaaS. The security services required for

the applications are obtained from an operator library. As presented in figure 8,

SECaaS allows

each network slice to be configured according to the client’s requirement, the application, and

the use case

(eMBB, mMTC, URLLC) to provide the resources (latency, bandwidth, QoS) and

security required.

For the NGMN Alliance in its work: “5G security recommendations Package # 2: Network

Slicing” there are several

challenges and solutions to the problem of security in NS 5G networks

which are presented in table 7.

4.2.6. Zero trust:

In Americas (2020), it is stated that the 5G architecture must implement the zero-trust

Novasinergia 2021, 4(1), 6-41 27

model (zero trust).

Zero trust is essential to mitigate security risks. Zero trust is based on the

concept of “denial by default” and assignment of

least privileges. According to John Kindervag,

one of the problems with security models is that they are based on the concept

of “trust and

verify.” In return, he proposes the concept of “verify and never trust” (Baker & Waldron, 2020).

This concept

allows 5G operators to restrict unnecessary access to specific network parts to

devices and users. In this sense, a network

operator could carry out some of its functions in its

systems and other functions in external infrastructures. The external cloud provider will be outside

the network operator’s trust model (5G Americas, 2020).

Figure 8: Security as a Service (SECaaS).

Table 7: Challenges and solutions of security in NS 5G networks.

No

Issue

Challenge

Recommendation

1

Controlling inter-

network slices

communications

Signaling and control traffic

between network segments. I/O

communications at user plane

level

All communications between slices and

functions should have a mechanism to control

their transmission and reception

2

Spoofing to network

slice manager

Spoofing attacks against the

network slice manager or

physical host plat- forms

Authenticate the network slice manager before

loading an NS instance.

3

Spoofing against a

network slice instance

Virtual functions contained

within a NS instance must be

authenticated and their integrity

verified.

NS managers should authenticate each other

within a carrier network before any

negotiation.

4

Different security

protocols or policies

If different slices offer different

ser- vices, you may have different

performance and security

requirements.

Implement a referential security level in all

slices, adequate isolation, and individual

authentication for a UE accessing several slices

at the same time.

5

Exhaustion of security

resources

Each slice must guarantee the

network resource for the security

protocols.

Guarantee the resources of a slice to execute

security protocols and policies without

exhausting resources in other slices.

6

Side-channel attacks

Prevent an attacker from being

able to extract information,

observe or influence how code

executes in functions in other

slices

Strengthen isolation between VMs and avoid

co-hosting on the same hardware slices with

different levels of vulnerability.

Novasinergia 2021, 4(1), 6-41 28

5. 5G research opportunities and developments

The standardization for 5G communication has been completed, and the 5G networks are

already becoming a commercial

reality (Tataria et al., 2021). Therefore, the research community is

starting to talk about beyond 5G communications referred

to as the sixth generation (6G) of

wireless networks. 6G networks are expected to provide critical features on the communication

services for future demands such as high security, secrecy, and privacy (Dang, Amin, Shihada, &

Alouini, 2020). Also, 6G

networks are expected to achieve the requirements of a fully connected

world and provide ubiquitous wireless connectivity

for everyone (Akyildiz, Kak, & Nie, 2020).

Hence, KPIs should be proposed to guide the design of 6G networks related to

those existing for

5G networks (Tataria et al., 2021). Table 8 shows a comparison of 5G and 6G networks KPIs and

main

features.

Table 8: Comparison of 5G and 6G networks KPIs and features (Dang et al., 2020; Tataria et al., 2021).)

KPIs/Features

5G

6G

Operating bandwidth

Up to 400 MHz (sub-6 Ghz

bands), Up to 3.25 GHz

(mmWave bands)

Up to 400 MHz (sub-6

Ghz bands), Up to 3.25

GHz (mmWave bands)

Maximum frequency

90 GHz

10 THz

Maximum data rate

35.46 Gbps

1 Tbps

User and control planes latency

1 ms (uRLLC), 20 ms

25 µs (tactile

applications), 20 ms

Mobility

500 km/h

1000 km/h

Architecture

Massive MIMO

Intelligent surface

Core networks

Internet, Internet of Things

Internet of Everything

Multiplexing

OFDMA

Smart OFDMA

Service level

3D VR/AR

Tactile

From the continuous evolution of 5G, new lessons will be learned. These lessons will serve as a

backdrop for emerging use

cases that will be better served by 6G such as remote healthcare, smart

environments, autonomous vehicles, space connectivity,

multi-sensory holographic teleportation,

industrial automation. Hence, to fulfill the 5G beyond vision, according to Akyildiz et

al. (2020),

several enabling technologies have been conceived and actively studied. Among these technologies,

the authors mentioned the following:

• A network operating at the THz band (with abundant spectrum resources),

• Intelligent communication environments,

• Pervasive artificial intelligence,

• Large-scale network automation,

• All-spectrum reconfigurable front-end (for dynamic spectrum access),

• Ambient backscatter communications (for energy savings),

• Internet of space things (CubeSats and UAVs),

• Cell-free massive MIMO communication networks,

• Internet of NanoThings and BioNanoThings,

• Quantum communications,

• Holistic security.

Concerning standardization initiatives for technologies and a network beyond 5G, the ITU has

recently established the ITU

focus group on technologies for network 2030 to study the capabilities

of future networks (2030 and beyond) and to provide guidance for developing the 6G network

(concepts, architecture, protocols, enabling technologies) (Akyildiz et al., 2020).

Novasinergia 2021, 4(1), 6-41 29

Although the research community and standardization entities are starting to discuss beyond 5G,

open challenges

and research opportunities remain to be developed. In the subsequent sections,

some additional research opportunities are

presented and the open challenges proposed in the

literature (see Table 1). Also, an overview of simulator tools and

testbed for conducting research

development on 5G networks is provided.

5.1. 5G research opportunities

Table 1 lists key open challenges proposed in the literature for research and development

in 5G technologies. Based on

our current research, we also consider the following research

opportunities regarding NS and random-a cce ss control in 5G

networks:

• NS enables new business opportunities across a wide range of use cases and sectors by making

it possible to create fit-

for-purpose virtual networks with varying degrees of independence,

as described in Section III. However, the diversity of

new business and technical requirements

has important implications for the way networks are built and managed, so there

is

considerable scope for studying different business models, especially in the PMVNOs.

PMVNOS offers functional ity beyond current offerings, which often rely on existing public

network services, which need to be studied in

terms of technical and economic feasibility.

• Access control (URLLC and mMTC) - One central 5G concept is fast, efficient, and scalable

random access, which can

handle many intermittent traffic-generating devices (such as IoT

devices) that are often inactive but periodically access

the network for minor updates with

no human interaction. Sporadic traffic will skyrocket in the 5G market, and the

bulky 4G

random access procedures will not handle it. Another 5G core principle is cell declassification,

combined with

cloud-powered baseband processing and wireless network visualization to

improve spectrum and energy efficiency and

manage expected traffic growth (Tello-Oquendo,

Lin, Akyildiz, & Pla, 2019; Tello-Oquendo, Akyildiz, Lin , & Pla , 2018).

More research is required to manage URLLC and mMTC in 5G efficiently; it is critical to

determine the appropriate

random access (RA) and/or access control mechanisms and how user

equipment performs self-uplink synchronization with

gNB to overcome preamble collisions caused

by multiple UEs transmitting the same preamble. Besides access control

mechanisms based on

barring schemes (Pacheco-Paramo & Tello-Oquendo , 2020; Pacheco-Paramo, Tello-Oquendo, Pla,

& Martinez-Bauset, 2019; Vidal, Tello-Oquendo, Pla, & Guijarro, 2019; Tello-Oquendo, Vidal, Pla, &

Guijarro, 2018; Tello-Oquendo, Vidal Catalá, Pla, & Martínez Bauset, 2018; Tello-Oquendo, Leyva-

Mayorga, Pla, Martínez-Bauset, & Casares-Giner, 2015), cooperative RA and other improvements to

the RA procedure are two other ways to support mMTC

in 5G. However, these may not be adequate

to meet URLLC MTC’s latency requirements. Complementing the existing

grant-based random

access (GBRA) method with grant-free random access (GFRA) protocol would be helpful to support

both mMTC and URLLC. Instead of contending with access requests for receiving a grant to

transmit the data packets,

UEs in GFRA contend with their data packets in a random-access

fashion; non-3GPP IoT solutions like LoRaWAN and

Sigfox use GFRA protocols extensively.

5.2. 5G research developments

Research and development of new and novel techniques and technologies for further

improving the spectral efficiency,

connectivity, and reliability of wireless communication

networks, require in-depth analysis and evaluation. Today, fixed and

mobile communications

specifications have become increasingly complex due to their demand for higher broadband data

Novasinergia 2021, 4(1), 6-41 30

rates

and challenging latency and reliability requirements, especially in emerging real-time

applications, like autonomous vehicles.

Thus, analytical techniques, as well as research-based on

link-level measurements, will soon encounter feasibility limitations (Muller et al., 2018). Therefore,

computer-aided numeric simulation is a technique of utmost importance to conduct research

and

develop new algorithms and future technologies in wireless communications (Müller et al., 2018;

Bouras, Gkamas, Diles, & Andreas, 2020). Table 9 summarizes the most relevant simulator tools to

evaluate the performance of

end-to-end 5G networks, new functionalities, and techniques at the

MAC and physical layers.

Navarro-Ortiz et al. (2020) provided detailed performance evaluation guidelines and use cases for

5G networks, including their corresponding scenarios and traffic models. The authors

recommended for research and proposals

in 5G communications, to employ, as the general use

cases for 5G performance evaluation, the five International Mobile

Telecommunications-2020

(IMT-2020) test environments (ITU, 2017): indoor hotspot- eMBB, dense urban-eMBB, rural-eMBB,

urban macro-mMTC, and urban macro-URLLC, using traffic patterns from the mobile and wireless

communications enablers

for the twenty-twenty information society (METIS) project (METIS, 2020).

An important task to conduct in a performance evaluation study is radio planning. For 5G networks,

Xirio Online is proposed in Aptica (2021). Xirio is a web simulator tool that provides the quickest

and cheapest way to perform 5G network planning using real maps based on the geographic

information system under urban and rural scenarios.

In addition to computer-based simulators, used to find the expected results of a hardware

configuration without the need

for actual implementation (Bouras et al., 2020), there are more and

more 5G testbeds from different laboratories that allow conducting tests closer to implementation.

Most of the testbeds are deployed in Europe (Informationsplattform for 5G, 2021). Table 10

summarizes

relevant testbeds available for research and development in 5G networks. The table

includes those references that provided

complete and online information about the testbed.

Table 9: Most significant 5G simulator tools.

Simulator

Module

Project

Language

Key features

NetSim

5G NR (Tetcos,

2021)

Proprietary

(fee)

C

Standard/Pro versions. 5G NR

simulation tool based on Release

15/3GPP 38 series. End-to-end

simulation of 5G networks. Support

5G Core (TS 23.501, TS23.502) functions

and interfaces, 5G NSA deployment,

SDAP spec. 37.324), RLC (spec. 38.322),

PDCP (spec. 38.323), MAC layer (spec.

38.321), physical layer (sub-carrier

spacing, numerologies, frame structure

& phy resources, carrier aggregation,

MIMO).

Ns-3

5G-LENA (CTTC,

2021)

Open

source

C++

NS-3 module to simulate 3GPP 5G

networks aligned with NR Release 15

TS 38.300. Support RLC (TS

38.322), P D C P (spec. 38.323), M A C layer

(TS

38.321, uplink delay support), physical

layer (numerology, mini-slot, and mixed

UL-DL slot format, propagation and

channel models, beamforming

methods, NR

PHY abstraction).

Novasinergia 2021, 4(1), 6-41 31

Table 9:

Continuation

.

Simulator

Module

Project

Language

Key features

Matlab

5G

Toolb

ox (MathWorks,

2021)

Proprietar

y (fee)

C/C++, Matlab

Simulator tool according to 3GPP 5G

NR specifications (Release 15 & 16).

Simulation of end-to-end 5G NR

communications links. Support 5G NR

physical layer (NR subcarrier and

numerology, propagation channel

models, Downlink and uplink channels

and signals, control information, and

transport channels).

Open5GCore

(Open5GCore, 2021)

Proprietary

(fee)

–

5G toolkit based on 3GPP Release 15

& 16 core network functionality (AMF,

SMF, AUSF, UDM, NRF,

UPF). Support standard 5G NR and UEs

[N1, N2,

N3], data path diversity (PFCP [N4]),

advanced session

management, network slice, non-3GPP

access.

Vienna 5G

Simulators

5G

System

Level

(Muller et al., 2018)

& 5G

Link

Level (Institute of

Telecommunications,

nd)

Academic

use

license

Matlab

Matlab based simulators. Support

multi-link, waveforms (CP-OFDM, f-

OFDM, FBMC, UFMC, WOLA), channel

codes (LDPC, turbo, polar,

convolutional), flexible numerology,

propagation, and channel models.

Open5GS

(Open5GS, 2021)

Open

source

C

Open-source tool that implements the

core network of NR/LTE network based

on Release-16.

Table 10:

Relevant testbed for 5G research development.

Testbed

Location

Frequencies

[GHz]

Use case

University of Bristol (5GINFIRE,

2021)

England

3.5, 26

Smarty City Safety

University of Surrey (University of

Surrey, 2021)

England

2.6, 3.5, 26

Satellite

5G-VINNI (Ghassemian,

Muschamp, & Warren, 2020; 5G-

PPP, 2021)

England

3.6, 2.6

Industry (Remote robotic

control, VR-based immersive

app), Cloud-based gaming,

Media,

e-Health (Connected

care), Public Protection

and

Disaster Relief

5G Lab (5G Industrielles Internet,

2021)

Germany

3.75, 26, 60

Industry 4.0 Applications,

Human-Machine

collaboration, Autonomous

driving, Robot-assisted

telesurgery

5G-EVE (5G Industrielles Internet,

2021)

Greece, Italy,

France

3.5, 3.6, 3.8

Industry 4.0 Applications,

Smart Cities, Smart

Campus,

Smart Transport

COSMOS (COSMOS GROUP, 2021)

USA

sub-6, 28

Smart city

Novasinergia 2021, 4(1), 6-41 32

Conclusions

This study reviewed some fundamentals of the 5G cellular network as architecture,

business models, cybersecurity, and

research developments. Concerning business models, this

article has described the different models that can be developed in

5G networks, especially those

based on network slicing; however, these may only be possible in 5G stand-alone versions,

as

well as others that may appear during the deployment of the 5G network. In the same sense, the

use cases described are

based on the stand-alone version of the 5G network (except those related

to spectrum sharing in non-standalone versions)

and whose key performance indicators are

devised to determine the end-to-end performance of the network. Computer-aided

numeric

simulation is mainly used to conduct research and develop novel proposals for further improving

spectral efficiency, connectivity, and reliability in 5G networks. However, in the last few years,

many 5G testbeds have

started to be offered from various laboratories to perform tests closer to

implementation within different verticals such as

industry 4.0 applications, smart cities, satellites.

Building a safe 5G network necessitates a comprehensive approach rather than

a narrow emphasis

on individual technical components. User authentication, traffic encryption, mobility, overload

conditions,

and network stability, for example, must all be considered together. Understanding

relevant risks and how to best manage them

is also essential. Enterprises embarking on a digital

transformation journey are most concerned about information security.

As a result, IoT must be

protected from the beginning, safeguarding personal information, business-sensitive data, and

vital

infrastructure. Industries must gather expertise, comprehend emerging risks, and mitigate

them to endure.

Authors’ contributions

Following the internationally established taxonomy for assigning credits to authors of

scientific articles (https://casrai.org/credit/). The authors declare their contributions in the following

matrix:

Aranda, J.

Sacoto

-Cabrera, E.

Haro-Mendoza. D.

Astudillo Salinas, F.

Conceptualization

Formal Analysis

Investigation

Methodology

Resources

Validation

Writing – review & editing

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