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Future Internet
Special Issues
5G Security: Challenges, Opportunities, and the Road Ahead
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5G Security: Challenges, Opportunities, and the Road Ahead

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".

Deadline for manuscript submissions: 10 April 2025 | Viewed by 13107

Special Issue Editors

Dr. Mario Di Mauro

E-Mail Website
Guest Editor
Department of Information and Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, 84084 Fisciano, Italy
Interests: network management; network security; availability; 5G; NFV
Special Issues, Collections and Topics in MDPI journals
Dr. Francesco Pascale

E-Mail Website
Guest Editor
Accenture S.P.A., Via Sciangai 53, Roma, Italy
Interests: Internet of Things; cybersecurity; knowledge management; bayesian network; recommender systems; embedded systems
Dr. Marco Tambasco

E-Mail Website
Guest Editor
Ericsson Telecomunicazioni S.p.A., Via Filettine 89, 84016 Pagani, SA, Italy
Interests: networks analysis and design; network availability and performance; cybersecurity

Special Issue Information

Dear Colleagues,

Security aspects are becoming of crucial importance across the hyperconnected technological world. In this context, 5G (and its evolution, 6G) represents a key network enabler for a plethora of paradigms, including Internet of Things (IoT), cyber-physical systems (CPSs), multi-access edge computing (MEC), network function virtualization (NFV), software-defined networking (SDN), and many others.

Due to the growing interest both of academia and industry in the broad field of security, for this Special Issue we encourage high-quality research contributions—both theoretical and experimental—and timely survey papers that pinpoint future research directions in this field.

Finally, I would like to thank Mr. Giovanni Galatro and his valuable work for assisting me with this Special Issue.

Topics of interest include, but are not limited to, the following:

  • Security protocols in 5G/6G architectures;
  • Privacy issues in 5G/6G architectures;
  • Security aspects in cloud/edge/fog computing;
  • Security aspects in multi-access edge computing (MEC);
  • Security aspects in the Internet of Things and/or cyber-physical systems;
  • Security management in modern virtualized networks (NFV, SDN, network slicing);
  • Access control mechanisms in modern networks;
  • Machine learning/artificial intelligence for 5G/6G network security;
  • Intrusion detection systems in 5G/6G networks;
  • Traffic analysis applied to 5G/6G networks;
  • Analytics and big data for network security;
  • Optimization techniques to improve 5G/6G network security;
  • Resilience strategies to improve 5G/6G network security;
  • Security aspects in 5G/6G vehicular communications;
  • Security aspects in millimeter-wave communications;
  • Security aspects in radio access networks (RANs);
  • Security aspects in 5G-oriented hardware (e.g., FPGA);
  • Security aspects in smart environments and industrial systems.

Dr. Mario Di Mauro
Dr. Francesco Pascale
Dr. Marco Tambasco
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

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16 pages, 1111 KiB  
Article
Design and Evaluation of Steganographic Channels in Fifth-Generation New Radio
by Markus Walter and Jörg Keller
Future Internet 2024, 16(11), 410; https://doi.org/10.3390/fi16110410 - 6 Nov 2024
Viewed by 466
Abstract
Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier [...] Read more.
Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat. Full article
(This article belongs to the Special Issue 5G Security: Challenges, Opportunities, and the Road Ahead)
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21 pages, 2684 KiB  
Article
Enhancing Network Security: A Machine Learning-Based Approach for Detecting and Mitigating Krack and Kr00k Attacks in IEEE 802.11
by Zaher Salah and Esraa Abu Elsoud
Future Internet 2023, 15(8), 269; https://doi.org/10.3390/fi15080269 - 14 Aug 2023
Cited by 3 | Viewed by 3220
Abstract
The rise in internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication networks from illegal [...] Read more.
The rise in internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication networks from illegal intrusions to guarantee data integrity and user privacy. In this situation, machine learning techniques used in data mining have proven to be effective tools for constructing intrusion detection systems (IDS) and improving their precision. We use the well-known AWID3 dataset, a comprehensive collection of wireless network traffic, to investigate the effectiveness of machine learning in enhancing network security. Our work primarily concentrates on Krack and Kr00k attacks, which target the most recent and dangerous flaws in IEEE 802.11 protocols. Through diligent implementation, we were able to successfully identify these threats using an IDS model that is based on machine learning. Notably, the resilience of our method was demonstrated by our ensemble classifier’s astounding 99% success rate in detecting the Krack attack. The effectiveness of our suggested remedy was further demonstrated by the high accuracy rate of 96.7% displayed by our neural network-based model in recognizing instances of the Kr00k attack. Our research shows the potential for considerably boosting network security in the face of new threats by leveraging the capabilities of machine learning and a diversified dataset. Our findings open the door for stronger, more proactive security measures to protect IEEE. 802.11 networks’ integrity, resulting in a safer online environment for all users. Full article
(This article belongs to the Special Issue 5G Security: Challenges, Opportunities, and the Road Ahead)
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16 pages, 4186 KiB  
Article
Deep Learning-Based Symptomizing Cyber Threats Using Adaptive 5G Shared Slice Security Approaches
by Abdul Majeed, Abdullah M. Alnajim, Athar Waseem, Aleem Khaliq, Aqdas Naveed, Shabana Habib, Muhammad Islam and Sheroz Khan
Future Internet 2023, 15(6), 193; https://doi.org/10.3390/fi15060193 - 26 May 2023
Cited by 7 | Viewed by 2114
Abstract
In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been adopted in order to counter such challenges. For 5G network defense, DL [...] Read more.
In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been adopted in order to counter such challenges. For 5G network defense, DL module are recommended here in order to symptomize suspicious NetFlow data. This module behaves as a virtual network function (VNF) and is placed along a 5G network. The DL module as a cyber threat-symptomizing (CTS) unit acts as a virtual security scanner along the 5G network data analytic function (NWDAF) to monitor the network data. When the data were found to be suspicious, causing network bottlenecks and let-downs of end-user services, they were labeled as “Anomalous”. For the best proactive and adaptive cyber defense system (PACDS), a logically organized modular approach has been followed to design the DL security module. In the application context, improvements have been made to input features dimension and computational complexity reduction with better response times and accuracy in outlier detection. Moreover, key performance indicators (KPIs) have been proposed for security module placement to secure interslice and intraslice communication channels from any internal or external attacks, also suggesting an adaptive defense mechanism and indicating its placement on a 5G network. Among the chosen DL models, the CNN model behaves as a stable model during behavior analysis in the results. The model classifies botnet-labeled data with 99.74% accuracy and higher precision. Full article
(This article belongs to the Special Issue 5G Security: Challenges, Opportunities, and the Road Ahead)
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Review

Jump to: Research

38 pages, 1021 KiB  
Review
A Systematic Survey on 5G and 6G Security Considerations, Challenges, Trends, and Research Areas
by Paul Scalise, Matthew Boeding, Michael Hempel, Hamid Sharif, Joseph Delloiacovo and John Reed
Future Internet 2024, 16(3), 67; https://doi.org/10.3390/fi16030067 - 20 Feb 2024
Cited by 8 | Viewed by 6085
Abstract
With the rapid rollout and growing adoption of 3GPP 5thGeneration (5G) cellular services, including in critical infrastructure sectors, it is important to review security mechanisms, risks, and potential vulnerabilities within this vital technology. Numerous security capabilities need to work together to ensure and [...] Read more.
With the rapid rollout and growing adoption of 3GPP 5thGeneration (5G) cellular services, including in critical infrastructure sectors, it is important to review security mechanisms, risks, and potential vulnerabilities within this vital technology. Numerous security capabilities need to work together to ensure and maintain a sufficiently secure 5G environment that places user privacy and security at the forefront. Confidentiality, integrity, and availability are all pillars of a privacy and security framework that define major aspects of 5G operations. They are incorporated and considered in the design of the 5G standard by the 3rd Generation Partnership Project (3GPP) with the goal of providing a highly reliable network operation for all. Through a comprehensive review, we aim to analyze the ever-evolving landscape of 5G, including any potential attack vectors and proposed measures to mitigate or prevent these threats. This paper presents a comprehensive survey of the state-of-the-art research that has been conducted in recent years regarding 5G systems, focusing on the main components in a systematic approach: the Core Network (CN), Radio Access Network (RAN), and User Equipment (UE). Additionally, we investigate the utilization of 5G in time-dependent, ultra-confidential, and private communications built around a Zero Trust approach. In today’s world, where everything is more connected than ever, Zero Trust policies and architectures can be highly valuable in operations containing sensitive data. Realizing a Zero Trust Architecture entails continuous verification of all devices, users, and requests, regardless of their location within the network, and grants permission only to authorized entities. Finally, developments and proposed methods of new 5G and future 6G security approaches, such as Blockchain technology, post-quantum cryptography (PQC), and Artificial Intelligence (AI) schemes, are also discussed to understand better the full landscape of current and future research within this telecommunications domain. Full article
(This article belongs to the Special Issue 5G Security: Challenges, Opportunities, and the Road Ahead)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Empowering UAV Network with Moving Target Defense and 5G-SDN: Security and Implementation Perspective
Authors: Ahmed Alismail; Huw Whitworth; Saba Al-Rubaye; Antonios Tsourdos; Liz James; Lawrence Baker
Affiliation: Cranfield University
Abstract: This paper is dedicated to bolstering the resilience of Unmanned Aerial Vehicle (UAV) networks against reconnaissance cyber-attacks. We present a novel algorithmic framework tailored for UAV networks, focusing on IP and Port hopping as a Moving Target Defense (MTD) strategy. This algorithm dynamically modifies IP addresses and communication ports, amplifying network unpredictability and frustrating reconnaissance efforts. We synergise Network-based Moving Target Defense with 5G Software-Defined Networking (SDN) for real-time network policy reconfiguration, facilitating proactive defense measures. Moreover, we incorporate honeypots as a cyber deception strategy, redirecting potential attackers and accumulating valuable insights into their methodologies. Extensive simulations validate the effectiveness of our approach in diminishing reconnaissance success rates and fortifying UAV network security.

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