Artificial Intelligence Security and Machine Learning

This Special Issue of Mathematics seeks to explore the rapidly evolving field of artificial intelligence (AI), with a focus on security aspects and machine learning techniques. AI and machine learning are integral for modern computational mathematics and intersect significantly with various domains, such as dynamic systems, engineering mathematics, and mathematical physics.

Dear Colleagues,

Artificial intelligence (AI) and machine learning (ML) are transforming every aspect of society, from healthcare and finance to engineering and the sciences. The integration of AI with traditional mathematical and engineering disciplines has paved the way for advanced analytical solutions and optimized decision-making processes. However, with great power comes great responsibility. The rapid deployment of AI systems necessitates robust measures to secure these systems against increasingly sophisticated threats. This Special Issue seeks to highlight research that not only advances the mathematical foundations of AI but also enhances its security and reliability.

The aim of this Special Issue is to curate a collection of high-quality research articles that address critical issues at the intersection of AI security and machine learning. We aim to showcase studies that have developed new mathematical models, computational algorithms, and practical applications that ensure the security and efficacy of AI systems. This Special Issue aligns with the journal’s focus on computational and applied mathematics, dynamic systems, and mathematical physics, contributing towards a deeper understanding of AI's capabilities and limitations.

Contributions are welcome in various formats, including original research articles, comprehensive reviews, and case studies. Suggested themes include, but are not limited to, the following:

• Theoretical foundations of AI and machine learning;
• Security challenges in machine learning algorithms;
• Cryptography and secure communication protocols in AI;
• AI in network security and intrusion detection;
• Robust machine learning algorithms against adversarial attacks;
• Application of fuzzy systems to secure AI frameworks;
• Decision-making and risk analysis in AI-driven systems;
• Bio-inspired security algorithms for machine learning;
• Integration of AI with sensor and electronic systems for enhanced security;
• Mathematical models for chaos and complexity in AI systems;
• Case studies on AI and ML applications in security-sensitive sectors (e.g., finance, healthcare, and telecommunications).

I am looking forward to receiving your contributions.

Prof. Dr. Xuemei Xu
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

• artificial intelligence
• machine learning
• AI security
• cryptography
• adversarial machine learning
• network security
• fuzzy logic
• risk analysis
• bio-inspired algorithms
• chaos theory