Network and Information Security

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 October 2025 | Viewed by 1235

Special Issue Editors


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Guest Editor
Department of Computer Science and Physics, Rider University, Lawrenceville, NJ 08648, USA
Interests: cybersecurity; quantum computing; Internet of Things; adversarial machine learning; artificial intelligence

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Guest Editor
1. College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
2. School of Engineering, College of Science, University of Lincoln, Lincoln LN6 7TS, UK
Interests: Internet of Things; sensor networks; green computing; cloud and fog computing; fault diagnosis; wireless sensor networks; multimedia communication; middleware; security
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Guest Editor
School of Computer Science, University of Oklahoma, Norman, OK 73019, USA
Interests: novel data-driven mobile/IoT system design; mobile and network security; machine learning for mobile network and security applications
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Guest Editor
Department of Computer Science, University of Missouri-Kansas City, Kansas City, MO 64110, USA
Interests: network security; Internet of Things; human-computer interaction

Special Issue Information

Dear Colleagues,

In an era defined by digital connectivity and technological innovation, the safeguarding of sensitive information and the protection of computer networks have become paramount concerns across industries, governments, and individual users alike. At the heart of this imperative lies the discipline of network and information security, an interdisciplinary field that blends elements of computer science, cryptography, telecommunications, and risk management to mitigate the ever-present threats to data integrity, confidentiality, and availability. As computer networks expanded in scale and complexity, driven by the proliferation of the Internet and advancements in telecommunications, the scope of security concerns broadened exponentially. Today, with the advent of cloud computing, mobile technology, and the Internet of Things (IoT), the landscape of digital threats has grown increasingly sophisticated and multifaceted.

In this Special Issue, we are pleased to invite front-line researchers and authors to submit original research and review articles on topics related to network and information security. Potential topics include the following:

  • Cybersecurity and Internet of Things;
  • Security of artificial intelligence;
  • Cyber-physical systems;
  • Security and privacy;
  • Security of system architecture and design;
  • Security algorithms;
  • Cryptography and network/information security;
  • Mobile system security;
  • Cloud computing security;
  • Protocols, systems, computers, and security;
  • Quantum computing and cybersecurity;
  • Post-quantum cryptography and security;
  • Privacy-preserving protocols and design.

Researchers working in the fields of network and information security and privacy are encouraged to submit original research papers. We look forward to receiving your contributions.

Dr. Zhengping Jay Luo
Prof. Dr. Lei Shu
Dr. Shangqing Zhao
Dr. Rui Duan
Guest Editors

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Keywords

  • cyber-physical system security
  • network/information security
  • mobile system security
  • cloud computing security
  • IoT security
  • AI security

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Published Papers (2 papers)

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Research

28 pages, 1783 KiB  
Article
Detection of TCP and MQTT-Based DoS/DDoS Attacks on MUD IoT Networks
by Nut Aroon, Luke Kane, Vicky Liu and Yuefeng Li
Electronics 2025, 14(8), 1653; https://doi.org/10.3390/electronics14081653 - 19 Apr 2025
Viewed by 134
Abstract
Mitigating cyberattacks on IoT networks is critical and remains a significant challenge, as such attacks can cause severe damage to the network systems and services. Moreover, the large volume of devices in IoT networks presents another challenge in managing security to reduce the [...] Read more.
Mitigating cyberattacks on IoT networks is critical and remains a significant challenge, as such attacks can cause severe damage to the network systems and services. Moreover, the large volume of devices in IoT networks presents another challenge in managing security to reduce the risk of attacks. The Manufacturer Usage Description (MUD) is a standard for limiting attack risks on IoT networks. However, MUD has limitations, as it relies solely on pre-defined access control list (ACL) rules to allow permitted traffic and block unknown traffic. This can lead to false-negative filtering, where malicious traffic may still be allowed by MUD, compromising an entire IoT network. This study presents the implementation of a network behaviour analysis (NBA) system for DoS/DDoS attack detection in MUD-based IoT networks. We designed a set of algorithms to enhance the effectiveness of malicious traffic detection compared to using MUD alone. The NBA system groups related traffic and detects a variety of DoS/DDoS attacks that utilise TCP and MQTT protocols. Our evaluation demonstrates that the NBA system achieves high detection accuracy, effectively identifying attacks that MUD alone would not be able to detect, thereby enhancing the effectiveness of attack detection in MUD-based IoT networks. Full article
(This article belongs to the Special Issue Network and Information Security)
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23 pages, 501 KiB  
Article
Advanced Network and System Security Teaching
by Mihajlo Ogrizović, Pavle Vuletić and Žarko Stanisavljević
Electronics 2025, 14(1), 3; https://doi.org/10.3390/electronics14010003 - 24 Dec 2024
Viewed by 637
Abstract
In an attempt to address the growing shortage of cybersecurity specialists in the country, the School of Electrical Engineering, University of Belgrade, started the course entitled Advanced Network and System Security (ANS) in the 2019/2020 school year. The ANS course covers the topics [...] Read more.
In an attempt to address the growing shortage of cybersecurity specialists in the country, the School of Electrical Engineering, University of Belgrade, started the course entitled Advanced Network and System Security (ANS) in the 2019/2020 school year. The ANS course covers the topics of computer system and network security, intrusion detection and prevention, and ethical hacking methodologies. This paper presents the course organization and associated laboratory environment and exercises and aims to prove that providing such a multidisciplinary laboratory leads to successful learning outcomes and directly improves gained knowledge in cybersecurity. The ANS course differs from all other related courses by covering various cybersecurity topics ranging from hardware through to network to web security. The analysis showed that 13 out of 19 Cyber Security Body of Knowledge classification Knowledge Areas are covered in the ANS course, unlike other related courses which cover up to 8 Knowledge Areas. Ultimately, the students’ practical skills improvement evaluation was performed through quantitative and qualitative analysis in order to prove that improving practical skills in the ANS laboratory resulted in the overall improvement of the gained knowledge. Full article
(This article belongs to the Special Issue Network and Information Security)
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