Description
Assignment Overview: In this assignment, you will act as a cybersecurity incidentresponder at a fictional organization, Tech Protect Inc. Your task is to respond to asimulated cybersecurity incident, conduct a thorough investigation, and produce adetailed incident response report. This assignment will evaluate your skills in incidentresponse, forensic analysis, and report writing. Do the report in Paper format. Papershould be 10 to 15 Pages, Double Spaced, APA Format.
Unformatted Attachment Preview
EXPERT (100%)
PROFICIENT (90%)
APPRENTICE(70%)
NOVICE (50%)
INTEGRATION
OF
KNOWLEDGE
(15%)
The paper
demonstrates that the
author fully
understands and has
applied concepts
learned in the course.
Concepts are
integrated into the
writer’s own insights.
The writer provides
concluding remarks
that show analysis
and synthesis of ideas.
The paper demonstrates that
the author, for the most part,
understands and has applied
concepts learned in the
course. Some of the
conclusions, however, are not
supported in the body of the
paper.
The paper demonstrates that the
author, to a certain extent,
understands and has applied
concepts learned in the course.
The paper does not
demonstrate that the author
has fully understood and
applied concepts learned in
the course.
TOPIC
FOCUS (15%)
The topic is focused
narrowly enough for
the scope of this
assignment. A thesis
statement provides
direction for the
paper, either by
statement of a
position or
hypothesis.
The topic is focused but lacks
direction. The paper is about
a specific topic but the writer
has not established a position.
The topic is too broad for the scope
of this assignment.
The topic is not clearly
defined.
DEPTH OF
DISCUSSION
(15%)
In-depth discussion &
elaboration in all
sections of the paper.
In-depth discussion &
elaboration in most sections
of the paper.
The writer has omitted pertinent
content or content runs-on
excessively. Quotations from others
outweigh the writer’s own ideas
excessively.
Cursory discussion in all the
sections of the paper or brief
discussion in only a few
sections.
COHESIVENESS
(15%)
Ties together
information from all
sources. Paper flows
from one issue to the
For the most part, ties
together information from all
sources. Paper flows with
only some disjointedness.
Sometimes ties together information
from all sources. Paper does not
flow – disjointedness is apparent.
Author’s writing does not
Does not tie together
information. Paper does not
flow and appears to be
created from disparate
next without the need
for headings. Author’s
writing demonstrates
an understanding of
the relationship
among material
obtained from all
sources.
Author’s writing demonstrates
an understanding of the
relationship among material
obtained from all sources.
demonstrate an understanding of the
relationship among material
obtained from all sources.
issues. Headings are
necessary to link concepts.
Writing does not
demonstrate understanding
any relationships
No spelling &/or
grammar mistakes.
Minimal spelling &/or
grammar mistakes.
Noticeable spelling & grammar
mistakes.
Unacceptable number of
spelling and/or grammar
mistakes.
SOURCES (15%)
More than 20 current
sources, of which at
least 15 are peerreview journal articles
or scholarly books.
Sources include both
general background
sources and
specialized sources.
Special-interest
sources and popular
literature are
acknowledged as such
if they are cited. All
web sites utilized are
authoritative.
20 current sources, of which
at least 10 are peer-review
journal articles or scholarly
books. All web sites utilized
are authoritative.
Fewer than 20 current sources, or
fewer than 5 of 20 are peer-reviewed
journal articles or scholarly books.
All web sites utilized are credible.
Fewer than 15 current
sources or fewer than 5 of
15 are peer-reviewed journal
articles or scholarly books.
Not all web sites utilized are
credible, and/or sources are
not current.
CITATIONS
(15%)
Cites all data obtained
from other sources.
IEEE citation style is
used in both text and
bibliography.
Cites most data obtained from
other sources.IEEE citation
style is used in both text and
bibliography.
Cites some data obtained from other
sources. Citation style is either
inconsistent or incorrect.
Does not cite sources.
SPELLING &
GRAMMAR
(10%)
Adapted from: Whalen, S. “Rubric from Contemporary Health Issues Research Paper”
http://academics.adelphi.edu/edu/hpe/healthstudies/whalen/HED601_r2.shtml
STRUCTRE OF YOUR PAPER.
ABSTRACT
150-250 words.
INTRODUCT ONE PAGE
RELATEDWORK ONE PAGE
BODY OF PAPER TWO PAGES: ARCHITECTURE/ IMPLEMENTION / EMPERICAL OR ANALYTICAL
DISCUSSION/CONCLUSION ONE PAGE
REFRENCES ONE PAGE
A Security Challenges and Opportunities for 5G and Beyond
Kamon Jernigan, Jorge M. Hurtado and Bharat S.Rawal
Cybersecurity Department
Benedict College
Columbia, South Carolina USA
(Kamon.Jernigan37, jorge.murillo87, bharat.rawal )@benedict.edu
Abstract- Mobile networks of the sixth generation
(6G) will need to be able to handle a variety of
threats in an environment with an integrated
space-air-ground network, unique technologies,
and an accessible user. the explosion of
information. Yet, for the time being, 6G security
and privacy concerns are mostly conceptual.
Based on potential 6G technologies at the
physical, connection, and service levels, as well as
lessons learned from the shortcomings of current
security designs and cutting-edge defenses, this
survey paper offers a thorough assessment of
security and privacy challenges. Here are the
next two key lessons. First, in addition to
inheriting flaws from previous generations, 6G
offers new risk vectors from new radio
technologies, such as the exposed location of
radio stripes in ultra-massive MIMO systems in
Terahertz
bands
and
attacks
against
omnipresent intelligence. Second, the most
promising techniques to significantly lower the
attack magnitude and data breaches include
bodily Layer protection, deep network slicing,
quantum-safe
communications,
artificial
intelligence (AI) security, platform agnostic
security, real-time adaptive security, and novel
data protection mechanisms like distributed
ledgers and differential privacy.
Key words : 5G, Network, Security, AI, 6G,
NextG
I.
Introduction:
The sixth generation, or 6G, of cellular
communications, is currently being developed to
replace the fifth generation or 5G. A bold picture of
6G’s fully autonomous networks that will be used for
commercial deployment in the 2030s is presented
[1]. 50 times faster than 5G, 6G will be able to
provide speeds of over 1Tbps, with 10-100 s
predicted latency [1]. Experts anticipate that this
standard will increase connectivity for both
traditional 5G coverage areas and applications using
space, air, ground, and sea. A wide range of digital
services, including wearable displays, implantable
technology, telepresence applications (which render
a 3D holographic representation of each meeting
participant), tactile Internet, mixed reality, and
autonomous driving will be made possible by the
coverage and network capacity. [2], [3], and [4],
respectively. With the significant rise in there are
serious worries that 6G security and privacy may be
worse than in prior generations due to coverage and
network heterogeneity. Consider the major privacy
risks raised by the integration of linked gadgets into
every area of human life (such as through implants
and cyborgs) (e.g., health records). Possible loss
from security attacks could be irrecoverable, not just
in terms of finances or reputation as they are now,
but also in terms of life (for example, a tragic
accident caused by an attack on autonomous
driving). Furthermore, extensive web surveillance
can be carried out using artificial intelligence
advancements [6]. Contrarily, cutting-edge
technologies like distributed ledgers and quantumsafe communications promise to greatly enhance 6G
security and privacy. Many people think that
advanced privacy and security technologies will be
crucial for success.
II.
Related Work:
Both relevant surveys and security and privacy for
6G are still in the early stages of development.
Current research on security and privacy issues can
be found in [7], [10], [16], and [17]. divided into
three categories: (1) security and privacy
preservation for IoT networks and their offshoots,
such as wireless sensor networks and vehicular
networks; (2) security and privacy concerns for
current 4G and 5G cellular networks; and (3)
security and privacy in 6G by examining concerns
related to particular key technologies, such as
machine learning. The subject of IoT security and
privacy is not new. The development of 6G may
involve a number of IoT security and privacy
solutions. For instance, the authors of [18] outline
many potential 6G technologies while addressing
security-related difficulties and sources of
vulnerabilities in IoT. asblockchain. A more
focused strategy is to address security in particular
network types that may exist in 6G, like automotive
networks [19] and IoT networks supported by 6G
[15], [20]. Discussions of particular 6G network
attacks are, however, fairly scarce as compared to
IoT security. Furthermore, many projections on the
security concerns for next-generation networks
favor referring to traditional risks such as sidechannel assaults and Distributed Denial-of-Service
(DDoS) attacks due to the limited understanding of
6G concepts at the time of the research of [21], [22].
A number of field studies, including security in 6G
heterogeneous vehicular networks [23], security in
tactile Internet [20], and security in edgecomputing-assisted IoT networks [24], suggest that
real-time protection and ultra-high reliability will be
important requirements for many applications in
future networks. Unfortunately, the discussions of
the surveys do not specifically mention 6G
communication paradigms or security architecture.
Due to the prevalence of mobile devices in our daily
lives, security and privacy issues for cellular
networks have received a lot of attention. The
majority of recent cellular network security and
privacy surveys are for 5G. For instance, the authors
of [7] and [10] provide different components of the
5G security architectural standards [8], [9], [38][40] relevant to security threats and privacy issues
on several levels, such as core/backhaul networks.
SDN [26], programmable networking, and Network
Function Virtualization (NFV) [17], [41], in
particular for Radio Access Networks (RAN) [42]
and Multi-access Edge Computing (MEC) [27],
[24], which promise to play the major roles, have
limits and security challenges. key topics in 6G that
have only been partially addressed. For our analysis
of the legacy technologies that affect 6G security
and privacy, the open discussions and technical
documents from various 5G security and privacy
surveys [10], [17], [26], and specific technologies
[25], [44] are crucial sources. The first five entries
in Table I are summaries of numerous cutting-edge
works in this area. Recently, interest in researching
new solutions for 6G security and privacy has
increased. The studies’ executive summaries of the
final twelve entries of Table I are listed in this
direction. Wang et al. [28] provide a summary of the
6G security and privacy vision via the lens of
upcoming applications, such as wireless braincomputer connections and multi-sensory XR
applications. This is closely related to our work. Yet
neither the technical discussion nor any specifics on
how AI is progressing in strengthening security are
included in that report. There is no mention of
connection and service layer security in Lymantria
et al. [29]’s description of various critical
technologies for 6G security and privacy, along with
the issues they still face. Nonetheless, numerous
writers have conducted surveys on more specific
topics,
including
quantum-safe
security
technologies [35], physical layer security [33], [34],
and [36]. The key priorities for 6G are said to be
trustworthy networks [30], AI-driven security [6],
[31], and [45]. The authors of [37] recently highlight
potential security and privacy issues with several 6G
technology and applications. There is, however, no
thorough analysis that offers a comprehensive view
of 6G security and privacy issues in the context of
overall security architecture, protection options in
the fundamental communication technologies, or
how they develop from legacy networks to satisfy
the new requirements in 6G applications.
Understanding the security transition and the
viability of potential technologies can help
operators, service providers, and developers
determine the best strategy for updating their
security infrastructure and defense systems at the
appropriate moment.
A singular opportunity exists with 6G to greatly
enhance security and privacy. To achieve this
purpose, there are two basic strategies. The first is to
safeguard 6G’s key supporting technologies, and the
second is to advance 5G’s is probably carried
through to 6G. Fig.3 shows a review of a few
potential technologies for improving 6G security
and privacy. Our vision categorizes these
evaluations based on the factors of automation,
dependability, privacy, and transparency. For
instance, a period transition with temporary
quantum-resistance cipher suites can be appropriate
before the complete quantum-safe TLS protocols
function. In the second scenario, switching to nuSIM
or non-ID for subscriber identity management may
be followed by the distribution of a subscription.
The technological positions can periodically change
depending on market demands and standards.
Figure 1. 5G/6G Security components []
The five generations of mobile networks are 1G, 2G,
3 G, 4G, and 5G, where G stands for Generation and
the number indicates the generation. The 1G
networks are now out of date, whereas 5G is the
most recent iteration. 2G, 3G, 4G, and 5G are made
possible by the cellular technologies GSM, UMTS,
LTE, and NR, respectively. The Global Times
newspaper claims that the satellite’s purpose is to
“check the terahertz (THz) communication
technology in orbit.” By 2030, 6G networks should
be developed and made available.
III.
Encoding & Cryptography
Interoperability between systems is ensured by
encoding. It enables information sharing between
systems that employ various data formats. Security
is not a goal of encoding. Data can be encoded and
decoded by anyone who understands the conversion
algorithm. The conversion algorithm’s identity is
made public. Cryptography, or cryptology, is the
practice and study of techniques for secure
communication in the presence of adversarial
behavior. More generally, cryptography is about
constructing and analyzing protocols that prevent
third parties or the public from reading private
messages. Any function that may be used to map
data of any size to fixed-size values is referred to be
a hash function, while some have functions that also
enable variable length output. Hash values, hash
codes, digests, or just hashes are the names given to
the results of a hash function.
IV.
6G and Quantum Cryptography
The article talks about the main computational
challenges we are facing that can’t be solved with
contemporary computing, especially on the Discrete
Logarithm Problem (DLP) which is the basis of
modern asymmetric cryptography. When quantum
computing becomes a reality on a daily base life,
these cryptographic primitives need to be replaced
with quantum-secure ones. Even though
contemporary symmetric cryptography still secures
most of the part. Asymmetric primitives based on
integer factorization and the DLP need to be
replaced[50].
Malware attacks are a problem that has been
increasing exponentially and becoming more
difficult to detect, that is because 5G networks have
multiple security flaws due to their reliance on 4G
network core The future 6G network is predicted to
be implemented with artificial intelligence-driven
communication via machine learning, enhanced
edge computing, post-quantum cryptography and so
forth. In the survey made in this article, the author
provided a roadmap, on 6G networks for data-driven
malware detection based on machine learning, and
the challenges that there will be[51].
With the arise of intelligent objects, future networks
of intelligent objects will come to life, as well as new
security challenges and opportunities to improve
security mechanisms. This article proposes a
roadmap towards realizing a new paradigm of
security that we as context-aware intelligent
security. The premise of this roadmap is that
detection and advanced AI will enable context
awareness, which in turn can lead to intelligent
security issues, such as adaptation and automation of
security[52].
5G networks are nowadays taking over 3G and 4G
networks due to the huge advances in technology,
and the need of adapting to work faster because we
are facing what we can call ever-improving
technologies. In terms of downloading, WIFI speed,
and IoT, it is expected that 5G and 6G will make it
wide open for new frequency ranges which will
result in many connections and huge data transfer
maintaining high network efficiency. When we talk
about 6G networks we must also bring up quantum
computing to the table because we are going to have
more
complex
challenges
but
security(cryptography) and speed connection which
soon are not going to be fulfilled with contemporary
computing[53].
5G security measures are more addressed to
2G/3G/4G network threats which include enhanced
authentication capabilities, subscriber identity
protection, and additional security techniques. But
this fifth network generation has introduced new
threats to industrial organizations. The number of
Mobile IoT connections increasing exponentially
means that “The IoT needs to be securely coded,
deployed and managed throughout its lifecycle”. IoT
devices are being used to form DDoS attacks where
each IoT device forms specific data resulting in
volume-based attacks. In 5G blockchain is
considered the main solution to many IoT security
problems [54].
5G does not suit future technical challenges that
must be solved for the generation 6G, the authors
propose to plan a security phase by using traditional
public key cryptography in 6G instead of
experimental technologies such as quantum
communications,
artificial
intelligence,
or
blockchain. Also, recommend that is time to speed
up the implementation of eSIMs due to the physical
limitations of SIMs for a virtual scenario. The
proposed scheme in this paper is simpler, easy to
implement, requires no third party, is cost-effective,
and utilizes algorithms that have proven their
security for decades without experimenting with
new techniques that can risk security [55].
5G is well-known for network cloudification with
micro-service-based
architecture,
the
next
generation networks, or the 6G era is closely
coupled with intelligent network orchestration and
management. 6G has a dilemma because while AI
applications are coded to protect, at the same time
can infringe on privacy. Future networks require
proactive threat detection, and application
mitigation to sustain self-sustainability in the 6G
era[56].
security and privacy are issues for 6G remain largely
in concept: inheriting vulnerabilities and threats
from previous generations and apart from that
having new technologies that are exposed to attacks
against pervasive intelligence. Second is physical
security, quantum-safe communications, artificial
intelligence (AI) security, and the need for novel
data protection mechanisms to mitigate attack
magnitudes and personal breaches [53].
Delivering 5G (the fifth generation) services
requires slicing a network, which is a crucial novel
element. The goal of 5G is to improve mobile
broadband and provide ultra-reliable, huge machinetype, low latency communications. This generation
is in charge of controlling the massive number of
Mobile Internet of Things devices (MIoT). In order
to counter the dangers, present in 2G, 3G, and 4G
networks, 5G has been developed. Improved
authentication capabilities, subscriber identity
protection, and additional security measures are
some of the 5G preventative measures. Industrial
enterprises are now facing new threats thanks to new
5G network technology[57].
The Mobile Internet of Things (IoT) demands better
security in 5G, according to the GSMA (The GSM
Association), as the number of IoT connections and
devices grows at an exponential rate. “The IoT must
be programmed, deployed, and managed in a secure
manner at all times.” its lifespan.” Common attacks
against IoT architecture include the following: 1)
Remote assaults over the internet; 2) attacks on IoT
devices through an application that is currently
executing; 3) physical assaults; 4) cloud-based
assaults 5) Wi-Fi or mobile air interface assaults.
Additionally, IoT devices are being employed in
volume-based DDoS attacks, where each IoT device
creates its own unique data. Blockchains are viewed
as the primary solution to a number of 5G
difficulties, including sharing issues with electronic
medical records and mobile IoT security challenges.
We examine post-quantum signatures based on
hashing for boosting blockchain security[57].
New developments in science and technology raise
the important question of “what’s next”. This wellknown truth has been reinforced by the development
of mobile networks and spectrum technologies
during the last two decades. The demand for a more
dependable, robust, intelligent, secure, and friendly
infrastructure has only increased due to the growing
need for wider frequency bands, connectivity of
devices that now number in the billions, and lower
latency (so that we can enjoy interruption-free
services around-the-clock), increasing involvement
of artificial intelligence in our daily lives, remote
connectivity, and virtual presence to increase our
output and reach, and many other factors. The
current 4G and 5G technologies are unable to
support the Internet of Everything’s expanding
connectivity and latency requirements[43].
Therefore, we describe the concept of 6G
technology together with its specifications in this
post and go into great detail about the related
difficulties and enabler technologies. But now that
quantum computers have been developed,
regardless of the underlying communication
technology used to ensure communication security
in current smart networks, all public-key-based
strategies are vulnerable to quantum assaults. In
order to actualize the secure and effective Internet of
Everything, case studies including the Internet of
Vehicles and the Internet of Things using a newly
proposed architecture based on quantum protected 6
G-enabled communication are described[43].
V.
SDN Security Architecture for Next G
network
A potential technology that provides centralized
management and programmability for networks is
software-defined networking (SDN), which can
enhance the security of wireless networks. An SDNbased security architecture can improve network
resource protection for NextG wireless networks,
stop unwanted access, and guarantee privacy. I’ll
give an overview of the NextG wireless networks’
SDN security architecture in this response and
mention some reliable sources to back up my points.
The NextG wireless network SDN security
architecture is made up of a number of parts that
work together to offer a complete security solution.
These elements
•
•
•
Network security policies are managed by the
SDN controller, which serves as the network’s
primary control point.
Security Policy Manager: The security policy
manager is in charge of creating and upholding
the network’s security policies. It interacts with
the SDN controller to guarantee that policies are
applied correctly.
Virtual Network Functions (VNFs): VNFs are
software-based network functions that are
•
•
deployable on-demand and can perform a
variety of security-related tasks, including
intrusion detection, firewalls, and encryption.
Network Access Control (NAC) is a security
tool that limits network access based on
predetermined restrictions, including user
identification, device type, and location.
Security Analytics: To identify and address
security threats, security analytics employs
machine learning and other cutting-edge
approaches.
Wireless network SDN-based security architectures
have been proposed and assessed in a number of
studies. In a paper by Alshammari et al. [58], for
instance, the authors suggested a VNF-based SDNbased security architecture for 5G wireless
networks. The analysis revealed that, in comparison
to conventional security solutions, the proposed
design enhanced security performance.
In a separate investigation, Wang et al. [59],
suggested an SDN-based security architecture for
industrial wireless networks that combined NAC
and security analytics to find and address security
threats. According to the study, the suggested
architecture increased network security and
decreased the danger of cyberattacks. The provision
of centralized control, programmability, and ondemand security deployment by an SDN-based
security architecture can improve the security of
NextG wireless networks.
I.
Analysis Discussion
6G privacy is important, but adequately preserving
it requires a lot of work. Privacy protection concerns
are not new and have been studied for a long time.
Massive data breaches happen virtually every day,
and technology hasn’t done much to address this
reality. Lack of sophisticated data protection and
poor data collection procedures by data collectors
are two of several factors that make it more difficult
to address these problems fully. Solving all of these
issues could take years or even longer if policies and
regulations do not keep up with modern society for
a lot of 6G applications.
Figure 3. Security Risk index in Given Industry[50]
Figure 4. Security level of Digital Signature
[49]
Figure 2. SDN security architecture for NextG
wireless network [54]
The process starts on the User side with the
International Mobile Subscriber Identifier and the
sequence number coming both of its data together,
then encrypts with the SIM’s public key and Seq#
private key. The IMSI and the seq# have to be
passed for authentication on the Service Provider
Network. When they are validated, the user can
decrypt the data requested.
Figure 5. Alternative Schemes For KEMs and PKI
[49]
right direction. To increase supply chain security,
several initiatives, including open RAN and opensource security, must be a success.
References
REFERENCES
Figure 6. The research invites level in various
countries [57]
Figure 7. Key security and privacy issues in 6G [57]
II.
Conclusions.
Mobile networks have been successful because of
their emphasis on security and privacy. When
everyone has access to the Internet in 6G, the
networks will become a vast, interconnected world
with a variety of enterprise and telecom networks,
both virtual and real, satellites, terrestrial nodes, and
other devices. We run a greater danger as the
networks become more complex. The proliferation
of connected devices and novel technologies may
make learning-powered assaults and big data
breaches more frequent in the 6G era, in addition to
more
conventional
security
issues
like
virus/malware/DDoS/deep fake. An overview of
security and privacy concerns with potential
technologies for the physical, connection, and
service layers of 6G has been offered in this paper.
We have described the survey’s key takeaways
below. a review of the potential solutions for 6G
security and privacy challenges, including
distributed ledgers, QKD, deep slicing, and physical
layer security. Energy efficiency and real-time
protection requirements, however, continue to be
important obstacles to such technology. Several 6G
security services are likely to fall short of their
objectives without these qualities. Last but not least,
we think that, although not a technological problem,
supply chain security will be crucial in ensuring that
the advancement of 6G security continues in the
[1] N. DOCOMO, “White paper: 5g evolution and 6g,”
Technical report, accessed on 10 August 2021.
[2] W. Saad, M. Bennis, and M. Chen, “A vision of 6g wireless
systems: Applications, trends, technologies, and open
research problems,” IEEENetwork, vol. 34, no. 3, pp. 134–
142, 2020.
[3] 5GIA, “Strategic research and innovation agenda 2021-27
– smart networks in the context of ngi,” European
Technology Platform NetWorld 2020, Sep 2020.
[4] S. Zhang and D. Zhu, “Towards artificial intelligence
enabled 6g: State of the art, challenges, and opportunities,”
Computer Networks, vol. 183,2020.
[5] F. Tang, Y. Kawamoto, N. Kato, and J. Liu, “Future
intelligent and secure vehicular network toward 6g:
Machine-learning approaches,” Proceeding of IEEE, vol.
108, no. 02, 2020.
[6] Y. Sun, J. Liu, J. Wang, Y. Cao, and N. Kato, “When
machine learning meets privacy in 6g: A survey,” IEEE
Communications Surveys & Tutorials, vol. 22, no. 4, pp.
2694–2724, 2020.
[7] M. A. Ferrag, L. Maglaras, and A. Derhab,
“Authentication and authorization for mobile iot devices
using biofeatures: Recent advances and future trends,”
Security and Communication Networks, 2019.
[8] 3GPP.SA3, “Technical specification group services and
system aspects; security architecture and procedures for 5g
system,” 3GPP TS 33.501 V16.4.0, 2020.
[9] M. Bartock, J. Cichonski, and M. Souppaya, “5g
cybersecurity -preparing a secure evolution to 5g,”
National Institute of Standardsand Technology, 2020.
[10] I. Ahmad, S. Shahabuddin, T. Kumar, J. Okwuibe, A.
Gurtov, and M. Ylianttila, “Security for 5g and beyond,”
IEEE Communications Surveys & Tutorials, vol. 21, no. 4,
pp. 3682–3722, 2019.
[11] G. Gui, M. Liu, F. Tang, N. Kato, and F. Adachi, “6g:
Opening new horizons for integration of comfort, security
and intelligence,” IEEE Wireless Communications, vol.
27, no. 5, pp. 126–132, 2020.
[12] P. Yang, Y. Xiao, M. Xiao, and S. Li, “6g wireless
communications: Vision and potential techniques,” IEEE
Network, vol. 33, no. 4, pp. 70– 75, 2019.
[13] Verizon,
“Dynamic
spectrum
sharing,”
https://www.fiercewireless.com/operators/verizon-ctowe-re-thrilleddss-performance, accessed on 10 August
2021.
[14] H.-N. Dai, Z. Zheng, and Y. Zhang, “Blockchain for
internet of things:A survey,” IEEE Internet of Things
Journal, vol. 6, no. 5, pp. 8076– 8094, 2019.
[15] F. Guo, F. R. Yu, H. Zhang, X. Li, H. Ji, and V. C. Leung,
“Enabling massive iot toward 6g: A comprehensive
survey,” IEEE Internet of Things Journal, pp. 1–1, 2021.
[16] S. A. et al., “6g white paper on machine learning in
wireless
communication
networks,”
https://arxiv.org/pdf/2004.13875.pdf, accessed on 10
August 2021.
[17] I. Farris, T. Taleb, Y. Khettab, and J. Song, “A survey on
emerging sdn and nfv security mechanisms for iot
systems,” IEEE Communications Surveys & Tutorials,
vol. 21, no. 1, pp. 812–837, 2019.
[18] N. Neshenko, E. Bou-Harb, J. Crichigno, G. Kaddoum,
and N. Ghani,“Demystifying iot security: An exhaustive
survey on iot vulnerabilities and a first empirical look on
internet-scale iot exploitations,” IEEE Communications
Surveys & Tutorials, vol. 21, no. 3, pp. 2702–2733,2019
[19] M. Hasan, S. Mohan, T. Shimizu, and H. Lu, “Securing
vehicle-toeverything (v2x) communication platforms,”
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
IEEE Transactions on Intelligent Vehicles, vol. 5, no. 4,
pp. 693–713, 2020.
N. Promwongsa, A. Ebrahimzadeh, D. Naboulsi, S.
Kianpisheh, F. Belqasmi, R. Glitho, N. Crespi, and O.
Alfandi, “A comprehensive survey of the tactile internet:
State-of-the-art and research directions,” IEEE
Communications Surveys Tutorials, vol. 23, no. 1, pp.
472–523, 2021.
T. M. Fernandez-Caram ´ es, “From pre-quantum to postquantum iot ´ security: A survey on quantum-resistant
cryptosystems for the internet of things,” IEEE Internet of
Things Journal, vol. 7, no. 7, pp. 6457– 6480, 2020.
J. Cao, M. Ma, H. Li, R. Ma, Y. Sun, P. Yu, and L. Xiong,
“A survey on security aspects for 3gpp 5g networks,” IEEE
Communications Surveys & Tutorials, vol. 22, no. 1, pp.
170–195, 2020.
Y. Hui, N. Cheng, Z. Su, Y. Huang, P. Zhao, T. H. Luan,
and C. Li,
“Secure and personalized edge computing
services in 6g heterogeneous vehicular networks,” IEEE
Internet of Things Journal, pp. 1–1, 2021.
A. Alwarafy, K. A. Al-Thelaya, M. Abdallah, J. Schneider,
and M. Hamdi, “A survey on security and privacy issues
in edge-computing assisted internet of things,” IEEE
Internet of Things Journal, vol. 8, no. 6, pp. 4004–4022,
2021.
Y. Dai, D. Xu, S. Maharjan, Z. Chen, Q. He, and Y. Zhang,
“Blockchain and deep reinforcement learning empowered
intelligent 5g beyond,” IEEE Network, vol. 33, no. 3, pp.
10–17, 2019.
J. C. C. Chica, J. C. Imbachi, and J. F. B. Vega, “Security
in
sdn: A comprehensive survey,” Journal of Network and
Computer Applications, vol. 159, 2020.
P. Ranaweera, A. D. Jurcut, and M. Liyanage, “Survey on
multi-access edge computing security and privacy,” IEEE
Communications Surveys & Tutorials, pp. 1–1, 2021.
M. Wang, T. Zhu, T. Zhang, J. Zhang, S. Yu, and W. Zhou,
“Security and privacy in 6g networks: New areas and new
challenges,” Digital Communications and Networks, vol.
6, pp. 281–291, 202
