Reliable and Secure AI Systems
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Security and Privacy".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 22
Special Issue Editors
Interests: artificial intelligence; cybersecurity; adversarial machine learning; adversarial signal processing
Interests: data security; medical images; cryptographic and watermarking tools
Interests: artificial intelligence; natural language processing; AI and NLP applications in smart cities
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
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
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 100 words) can be sent to the Editorial Office for announcement on this website.
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information 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
- adversarial machine learning
- trustworthy AI
- AI security and privacy
- robust and explainable AI
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