Intrusion Detection and Resiliency in Cyber-Physical Systems and Networks

Dear Colleagues,

In an increasingly connected world, cyberattacks represent stealthy and often devastating intrusions into networks, systems, and infrastructure. These attacks have evolved in sophistication and frequency, leading to severe consequences such as security breaches, financial losses, and compromised critical systems. Addressing these challenges requires innovative and robust intrusion detection methods that enhance the security and resilience of cyber–physical systems and networks. This Special Issue invites researchers to contribute original and impactful research focusing on intrusion detection techniques and novel approaches in cybersecurity. Emphasis is placed on leveraging cutting-edge technologies, such as artificial intelligence (AI), machine learning, blockchain, and quantum security, to address contemporary threats effectively. Additionally, methods that ensure resiliency and adaptability in cyber–physical systems are of particular interest, especially those operating in dynamic and adversarial environments.

We will provide a platform for interdisciplinary research that bridges gaps between traditional cybersecurity practices and emerging AI and system resiliency techniques. Contributions addressing practical applications in industries such as smart cities, healthcare, transportation, and energy systems are especially welcome.

We invite high-quality research articles, reviews, and case studies. Contributions should present theoretical innovations, practical applications, or both, with clear implications for advancing security and resiliency in cyber–physical systems and networks. We encourage submissions that address, but are not limited to, the following topics:

• Machine Learning and Federated Learning: Application of centralized and decentralized machine learning methods to enhance intrusion detection across distributed systems;
• Resiliency and Robustness: Techniques to ensure systems remain operational despite ongoing attacks or failures;
• Quantum Security: Novel cryptographic techniques to safeguard systems against quantum-computing-based threats;
• Adversarial Learning: Strategies to mitigate the impacts of adversarial attacks on AI models;
• Deep Fake Detection: Identifying and mitigating threats posed by deep fake technologies in communications and operations;
• Intrusion Detection: Development of scalable, efficient, and accurate methods for detecting unauthorized access;
• Data Breaches and Privacy Preservation: Techniques to prevent data breaches while maintaining user privacy;
• Malware Analysis and Detection: Advanced approaches for identifying and neutralizing malware threats;
• Sybil Attacks and Byzantine Faults: Detection and prevention of attacks targeting distributed systems and blockchains;
• Ransomware Mitigation: Strategies to detect and respond to ransomware attacks;
• Blockchain Technology: Leveraging blockchain for secure data sharing and intrusion detection;
• Honeypots: Deployment and analysis of honeypots for luring and studying attackers;
• Trustworthy AI: Ensuring AI systems are secure, interpretable, and resilient to attacks;
• Differential Privacy and Anonymization: Techniques to maintain user anonymity while analyzing sensitive data;
• Large-Language Models (LLMs): Utilizing and safeguarding advanced AI models in intrusion detection;
• Phishing Attack Countermeasures: Strategies to identify and neutralize phishing threats effectively.

Dr. Olusola Tolulope Odeyomi
Dr. Temitayo Olowu
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.

• intrusion detection
• cyber–physical systems
• machine learning
• federated learning
• adversarial learning
• intrusion detection
• malware detection
• blockchain technology
• trustworthy AI
• large-language models