IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT)

3-5 Dec 2025 · Osaka, Japan.

http://www.ieee-qcnc.org/2025

Track 4: Security, Trust, Privacy in AI and IoT

Track Chairs:
Jiawei Yuan, University of Massachusetts Dartmouth, USA, jyuan@umassd.edu
Saed Alrabaee, United Arab Emirates University, UAE, salrabaee@uaeu.ac.ae
Thomas Tan, Edinburgh Napier University, UK, Z.Tan@napier.ac.uk

Description

AI techniques have revolutionized many aspects of the Internet of Things (IoT) with their powerful generation, contextual understanding, and multi-modal processing. The integration of AI and IoT devices has created a new interaction paradigm that efficiently integrates human needs with machine intelligence, significantly improving efficiency and quality of intelligent services. However, the combination of AI and IoT devices also introduces security, trust, and privacy issues. It is challenging to safeguard the security, trust, and privacy of these devices due to the IoT devices’ variety, the complex structure of AI models, and the diversity of data. To address these challenges, this track invites submissions of original research papers from both academia and industry practitioners that present novel contributions in algorithms, system designs, implementations, and evaluations. We welcome papers in these and related areas.

Track Topics

• AI-enhanced Authentication for IoT Devices
• AI-based Access Control for IoT
• AI for Truth Verification and Management in IoT
• AI for Data Privacy in IoT Devices and Services
• Federated Learning in IoT Security
• Edge-Deployed AI Security in IoT
• Incentive Strategies for AI Interaction in IoT
• AI Applications for Smart City IoT Security
• Data Security for AI-powered IoT
• Privacy-enhancing Technologies in Intelligent IoT Systems
• AI-enabled Attacks and Defenses for IoT Devices and Services
• AI for Communication Security of IoT Devices
• Malware Analysis for Intelligent IoT
• Vulnerability Analysis for AI-integrated IoT Devices
• Intelligent Forensics Tools, Techniques, and Procedures for IoT
• Emerging Data Bias Security Issues in Intelligent IoT Systems
• Lightweight Hardware Verification in Intelligent IoT Systems
• Side-Channel Attacks and Defense in Intelligent IoT Systems
• The implications of machine unlearning for security, trust, and privacy in AI and IoT

Paper Submission and Publication

Details of paper submission and publication can be found here.