Artificial Intelligence Techniques for IoT Security and Privacy
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 390
Editor
Special Issue Information
Dear Colleagues,
The rapid growth of the Internet of Things (IoT) and the increasing integration of artificial intelligence (AI) into connected systems have transformed how data is generated, analysed, and acted upon. While these advances enable intelligent, autonomous, and data‑driven applications, they also introduce significant cybersecurity, privacy, and trust challenges. IoT environments are highly distributed, heterogeneous, and resource‑constrained, making them particularly vulnerable to attacks and difficult to secure using conventional approaches.
This Special Issue aims to present novel research on AI‑driven methods for enhancing IoT security and protecting privacy, from theoretical foundations to practical deployment. We invite original research articles and review papers that investigate the use of machine learning, deep learning and large language models (LLMs) for intrusion detection, anomaly and behavioural analysis, threat intelligence and adaptive security in IoT systems. Contributions focusing on privacy‑preserving AI, adversarial robustness and trustworthy intelligence across edge, fog and cloud‑based IoT architectures are particularly welcome.
Topics of interest include, but are not limited to:
- AI‑based intrusion detection systems for IoT
- Behavioural and anomaly analysis
- Adversarial machine learning
- Privacy‑aware and trustworthy AI
- LLMs for security analysis
- Secure and resilient IoT architectures
Dr. Áine MacDermott
Guest Editor
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Keywords
- Internet of Things (IoT)
- cybersecurity
- privacy
- trust
- artificial intelligence (AI)
- anomaly detection
- resilience
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