Network Forensics and Cybersecurity Applications
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "AI Systems: Theory and Applications".
Deadline for manuscript submissions: 30 April 2027 | Viewed by 165
Editors
Interests: wireless sensing; cyber-physical systems and their security; human-machine systems and their security
Interests: wireless sensing; artificial intelligence; cyber–physical system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid integration of Artificial Intelligence (AI) into modern network architectures has revolutionized the landscape of digital security and forensic investigation. As we transition toward 6G and the Internet of Everything (IoE), the boundary between cyberspace and physical space is blurring, giving rise to complex Cyber-Physical Systems (CPS), from autonomous robotic systems to smart critical infrastructures. These emerging environments introduce unprecedented security challenges, including sophisticated physical-layer eavesdropping, unauthorized wireless sensing, and AI-driven signal manipulation. This Special Issue aims to provide a platform for researchers to present cutting-edge AI methodologies that address the evolving needs of network forensics and cybersecurity. We are particularly interested in how AI can enhance the traceability, attribution, and resilience of networks against both conventional cyber-attacks and emerging physical-domain threats. We welcome studies that utilize advanced techniques, such as Physics-Informed Neural Networks (PINNs), contrastive learning, and generative models to secure the "neural pathways" of modern information systems. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: AI-driven forensic analysis for 6G, ISAC, and IoT ecosystems; Cybersecurity applications for critical infrastructures (e.g., smart grids, V2G systems); Detection and localization of unauthorized wireless sensing and hidden surveillance devices; Privacy-preserving AI for forensics in human-centric cyber-physical systems; Physical-layer security and cross-layer forensic attribution techniques; Robustness and adversarial defense in AI-based intrusion detection systems; Network traffic fingerprinting and anomaly detection using deep representation learning. We look forward to receiving your contributions.
Dr. Xiang Zhang
Dr. Huan Yan
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI 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 1800 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.
Keywords
- network forensics
- cybersecurity applications
- artificial intelligence
- cyber-physical systems (CPS)
- wireless sensing security
- 6G-ISAC Physics-Informed Neural Networks (PINNs)
- intrusion detection
- critical infrastructure protection
- privacy preservation
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