IEEE CEM 2024 : IEEE Consumer Electronics Magazine - Special Issue Call for Articles -Adversarial Examples in CE: Deceptive Threats to AI Systems

Background & Motivation:
Artificial Intelligence (AI) has found extensive applications in various domains of Consumer Electronics (CE), including FinTech, smart homes, autonomous driving, information security, and so on. It encompasses various data types such as voice, Natural Language Processing (NLP), images, videos, wireless radio-frequency signals, and more. AI excels in feature extraction, prediction, and recognition across these diverse data types. In essence, humanity has become inseparable from AI. In this context, attackers have shifted their focus to the core of AI, creating Adversarial Examples (ADV) that escape human perception, with the intention of deceiving AI models. These versatile ADVs can be concealed within various data types. The development of such attacks poses a significant threat to humanity, particularly in a scenario where our dependence on AI continues to grow.

Scope’s Significance:
This special issue is dedicated to "AI Security and Privacy of CE Hardware and Software Systems (AI-SPC)." We welcome submissions on various aspects, including attacks design, predictions, and preventive measures related to ADVs in CE across different domains. Topics of interest include but are not limited to:
1. Identification and Defense Against ADVs in Biometric Payment Systems (e.g., fingerprint, voiceprint, facial recognition) within FinTech CE.
2. Impact of ADVs on Autonomous Driving Safety and Mitigation Strategies.
3. ADVs in Fake News Detection.
4. Identification of Counterfeit Radio-Frequency Base Stations Based on ADVs.
5. Advancements in ADV Techniques Using Various AI/ML and Metaheuristic Algorithms.
6. Exploring Explainable AI (XAI) in the Context of ADVs.
7. Novel ADV Attack Designs in the AI-SPC Domain.
8. Adversarial Training Techniques in AI-SPC.
9. ADV Attacks and Defenses in Reinforcement Learning or Federated Learning.
10. Value-Added Applications of ADV-Related Research in Various CE Domains.

Timeliness:
The rapid advancement and widespread adoption of artificial intelligence have made AI systems susceptible to emerging ADV. Furthermore, ensuring the security and privacy of personal data and critical infrastructure in CE products is of paramount importance. Even brief security vulnerabilities can lead to far-reaching consequences, underscoring the necessity for immediate research to safeguard these technologies and information.

Relevance to the IEEE CEM:
CEs are increasingly relying on AI to enhance human user experiences, spanning across critical domains such as FinTech, autonomous driving, and smart homes. Consequently, the vast CEs market has become a breeding ground for ADV. These attacks can compromise the integrity of the CEs domain, posing serious cybersecurity risks, including the leakage of personal information. By delving into ADV attack techniques, prevention methods, and mitigation strategies in the realm of CEs, this special issue aims to provide valuable insights and knowledge for IEEE CEM readers.

Tentative Schedule
Manuscript submission deadline: March 1,
2024; Authors’ Revision Notification Date: June 1, 2024;
Revised Manuscript Submission Deadline: July 15, 2024;
Final Decision Notification Date: September 1, 2024;
Publication Date: March 1, 2025

Lead guest editor
Chia-Mu Yu ([email protected])
Department of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University, Taiwan

Guest editors
Hsin-Hung Cho ([email protected])
Department of Computer Science and Information Engineering at National Ilan University, Taiwan
Reza Malekian ([email protected])
Department of Computer Science and Media Technology, Malmö University, Sweden
Alireza Jolfaei ([email protected])
College of Science and Engineering, Flinders University , Australia
Lei Shu ([email protected])
Nanjing Agricultural University, China/ University of Lincoln, UK