Reliable and Secure AI Systems

Dear Colleagues,

Artificial intelligence (AI) is transforming various sectors, from healthcare and finance to autonomous systems and cybersecurity.; however, ensuring the reliability and security of AI-driven solutions has become a critical challenge. AI models are increasingly being deployed in sensitive applications where adversarial threats, biases, and system vulnerabilities can lead to severe consequences, including misinformation, security breaches, and compromised decision-making processes.

This Special Issue, “Reliable and Secure AI Systems”, aims to address these pressing concerns by compiling innovative research on AI robustness, adversarial machine learning, trustworthy AI, and security-aware AI deployment. Key topics of interest include, but are not limited to, adversarial machine learning including attacks and defenses, adversarial resilience in deep learning, secure federated learning, privacy-preserving AI, ethical AI frameworks, and formal verification techniques for AI systems. This Special Issue additionally seeks to explore novel attack and defense mechanisms against emerging AI threats and ways to make sure that AI systems remain transparent, explainable, and aligned with security best practices.

We invite researchers and practitioners from academia and industry to contribute their latest findings in the pursuit of building AI systems that are not only intelligent but also secure, robust, and trustworthy.

Dr. Kassem Kallas
Dr. Reda Bellafqira
Dr. Kashif Ahmad
Guest Editors

Manuscript Submission Information

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