Advances and Challenges of ML & DL in Cybersecurity

By: S. L. Jany Shabu

The integration of cybersecurity and intelligent systems, highlighting how machine learning (ML) and deep learning (DL) enhance modern cyber defense. It introduces foundational cybersecurity concepts, the evolution of threats and defenses, and core ML principles such as data collection, preprocessing, learning algorithms, and challenges including data imbalance, concept drift, scalability, and robustness. The text explores deep learning architectures and their applications in intrusion detection, threat intelligence, and malware analysis, emphasizing anomaly detection, automated threat analysis, and resilience against evasion. It also addresses adversarial machine learning, model robustness, ethical and legal considerations, privacy, and interpretability. The book concludes with emerging AI technologies, autonomous defense systems, and future research directions for building resilient and explainable AI-driven cybersecurity solutions.

• Format: Paperback
• Language: English
• ISBN: 6209654347
• ISBN13: 9786209654343
• Release Date: February 2026
• Publisher: LAP Lambert Academic Publishing
• Length: 128 Pages
• Weight: 0.40 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"