Advanced Artificial Intelligence and Machine Learning for Cybersecurity

Dear Colleagues,

In recent years, the prevalence of cyber threats and attacks has escalated dramatically, posing a serious threat to global security. These threats manifest in various ways, including data breaches, phishing schemes, identity theft, misinformation/disinformation, financial fraud, and attacks on critical infrastructure, affecting countless individuals and organizations. The growing sophistication and frequency of these cyber-attacks highlight the urgent need for advanced artificial intelligence (AI)-driven cybersecurity measures and constant vigilance in the digital landscape.

The term “cybersecurity” refers to the technologies and practices developed to protect computer systems, networks, and data from digital attacks, unauthorized access, and damage. It includes various protective measures such as encryption, setting up firewalls, and continuously monitoring systems to maintain the safety and privacy of data. In today’s digital world, advanced artificial intelligence (AI) and machine learning, spanning generative AI, large language models (LLMs), automated ML (AutoML), adversarial ML, online/continual learning, federated learning, TinyML, explainable AI, and agentic AI, are becoming powerful cybersecurity tools. They can help to automate complicated security tasks, assist in identifying and analyzing cyber threats, and simulate advanced cyber-attacks to improve training and readiness. Furthermore, advanced AI and machine learning play a role in creating defense strategies for new types of cyber threats, including those involving misinformation and deepfakes, as well as rapidly evolving threats in dynamic networks, IoT, edge, and cyber–physical systems.

For this Special Issue, we are seeking submissions of original, unpublished articles that address recent advances in advanced AI and machine learning for cybersecurity, from trustworthy and robust learning to scalable deployment in real-world systems. Authors are invited to submit manuscripts addressing the development of AI and machine learning methods for simulating cyber threats, designing cyber defense, and analyzing cyber forensics. We welcome contributions that span cloud-to-edge deployment, resource-constrained intelligence, and learning under limited labels, privacy constraints, and distribution shifts. Technical papers, reviews, surveys, and case studies are encouraged. Topics of interest include (but are not limited to) the following:

• AI-driven threat detection and analysis;
• Generative models for threat simulation and cyber-attack training;
• Countermeasures and defenses against AI-generated cyber threats;
• Generative AI in cyber forensics;
• Integrating AI with existing cybersecurity frameworks;
• Generative AI in risk assessment;
• The ethical implications of AI in security;
• Generative AI for misinformation/disinformation;
• LLMs and generative AI for cybersecurity and securing LLM-based systems;
• Deepfake detection and mitigation;
• Responsible AI in cybersecurity;
• AutoML for intrusion and malware detection;
• Multi-objective learning for security accuracy efficiency robustness;
• TinyML and edge AI for IoT IIoT and critical infrastructure security;
• Online and continual learning for evolving threats and concept drift;
• Federated and privacy-preserving learning for collaborative defense;
• Adversarial machine learning;
• Explainable AI for cybersecurity decision support and auditing;
• Agentic AI for autonomous detection investigation and response.

Dr. Raha Moraffah
Dr. Li Yang
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 250 words) can be sent to the Editorial Office for assessment.

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. Future Internet 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.

• artificial intelligence
• advanced AI
• advanced machine learning
• generative AI
• large language models (LLMs)
• AutoML
• TinyML
• online learning
• continual learning
• federated learning
• adversarial machine learning
• trustworthy AI
• responsible AI
• cyber-attacks
• cyber defenses
• intrusion detection
• malware analysis
• risk assessment
• misinformation
• cyber security