AI, Machine Learning (ML), and Large Language Models (LLMs) for Cybersecurity in Sensor Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".
Deadline for manuscript submissions: 15 January 2026 | Viewed by 206
Special Issue Editor
Interests: AI; ML; LLMs; cybersecurity; NextGen Netoworks; IoT; sensor network
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The increasing sophistication of cyber threats necessitates advanced security solutions driven by Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs). This Special Issue explores the latest research in AI-driven cybersecurity, including threat detection, intrusion prevention, anomaly detection, and automated response mechanisms. By leveraging AI and LLMs, researchers and practitioners can develop more adaptive and intelligent security frameworks to combat evolving cyber risks.
This Special Issue invites contributions related to AI-enhanced security strategies, deep learning applications, adversarial machine learning, and the ethical considerations surrounding AI in cybersecurity. Topics include real-time phishing detection, malware analysis, network security, and privacy-preserving AI techniques. This Special Issue aims to provide a comprehensive overview of cutting-edge advancements in AI-powered cybersecurity solutions, aligning with the scope of Sensors.
Dr. Robin Chataut
Guest Editor
Manuscript Submission Information
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Keywords
- AI for cybersecurity
- machine learning in security
- large language models (LLMs)
- intrusion detection and prevention
- phishing and malware detection
- adversarial AI in cybersecurity
- privacy-preserving AI techniques
- behavioral anomaly detection
- cyber threat intelligence
- automated security response
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