New Trends in Artificial Intelligence-Based Cybersecurity
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 April 2026 | Viewed by 12
Special Issue Editors
Interests: natural language processing; BERT; transfer learning; classification; cybersecurity; CYVET; convolution neural network; accuracy maximization
Interests: adversarial machine learning; counter-AI methods; static binary instrumentation; machine learning-based malware; cyber defense evasion
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) is rapidly transforming the cybersecurity landscape, providing powerful capabilities to defend against evolving threats while also creating new vulnerabilities. This Special Issue seeks to present a comprehensive overview of AI-based cybersecurity research and applications, exploring how AI techniques can fortify defenses as well as the risks and challenges that emerge when attackers exploit AI. We invite contributions that bridge theory and practice, highlighting cutting-edge advances in both AI for security and security for AI. The scope is interdisciplinary, drawing perspectives from computer science, information security, data science, operations research, and related fields. By assembling state-of-the-art studies, this Issue aims to deepen understanding of how AI can be applied to detect, prevent, and respond to cyber threats, while also addressing the ethical, regulatory, and practical considerations of integrating AI into security systems. Ultimately, the goal is to equip both researchers and practitioners with the insights needed to harness AI in building more resilient cybersecurity frameworks in an era of increasingly intelligent adversaries.
This Special Issue will focus on (but is not limited to) the following topics:
- AI-Driven Threat Detection and Analysis.
- AI-Enhanced Threat Intelligence and Predictive Security.
- AI-Enabled Incident Response and/or Recovery.
- Security for AI Systems.
- Understanding, Detecting, and Mitigating AI-Generated Malware.
- Emerging AI Techniques in Cybersecurity.
- Applications of Large Language Models (LLMs) and Reinforcement Learning (RL) in Cybersecurity.
- Explainable AI (XAI) Approaches in Cybersecurity.
- Ethical, Legal, and Regulatory Issues in AI-Based Security.
Dr. Juan Lopez Jr.
Dr. Luke Koch
Dr. Sean Oesch
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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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
- artificial intelligence (AI)
- cybersecurity
- threat detection
- threat intelligence
- predictive security
- incident response
- recovery
- security for AI
- AI-generated malware
- emerging AI techniques
- large language models (LLMs)
- reinforcement learning (RL)
- explainable AI (XAI)
- ethics
- regulation
- legal issues
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