Artificial Intelligence for Intrusion Detection Systems

 
Edition number: 1
Publisher: Chapman and Hall
Date of Publication:
 
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Short description:

This book is aligned with the cyber security issues and provides a wide view of the novel cyber-attacks and the defence mechanisms, especially AI-based IDS.

Long description:

This book is associated with the cybersecurity issues and provides a wide view of the novel cyber attacks and the defense mechanisms, especially AI-based Intrusion Detection Systems (IDS).


Features:



  • A systematic overview of the state-of-the-art IDS

  • Proper explanation of novel cyber attacks which are much different from classical cyber attacks

  • Proper and in-depth discussion of AI in the field of cybersecurity

  • Introduction to design and architecture of novel AI-based IDS with a trans- parent view of real-time implementations

  • Covers a wide variety of AI-based cyber defense mechanisms, especially in the field of
    network-based attacks, IoT-based attacks, multimedia attacks, and blockchain attacks.

This book serves as a reference book for scientific investigators who need to analyze IDS, as well as researchers developing methodologies in this field. It may also be used as a textbook for a graduate-level course on information security.

Table of Contents:
1. Intrusion detection system using artificial intelligence. 2. Robust, Efficient and Interpretable Adversarial AI Models for Intrusion Detection in Virtualization Environment. 3. Detection of Malicious Activities by Smart Signature-based IDS. 4. Detection of Malicious Activities by AI-supported Anomaly-based IDS. 5. An Artificial Intelligent Enabled Framework for Malware Detection. 6. IDS for Internet of Things (IoT) and Industrial IoT Network. 7. An Improved NIDS using RF based feature selection technique and voting classifier. 8. Enhanced AI-based Intrusion Detection and Response System for WSN. 9. Methodology for Programming of AI-based IDS.