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Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence [Kõva köide]

Edited by , Edited by (Sultan Moulay Slimane University, Morocco), Edited by (Charles Darwin University, Australia), Edited by
  • Formaat: Hardback, 280 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 44 Tables, black and white; 87 Illustrations, color; 7 Illustrations, black and white
  • Ilmumisaeg: 28-Apr-2023
  • Kirjastus: River Publishers
  • ISBN-10: 8770227780
  • ISBN-13: 9788770227780
Teised raamatud teemal:
Big Data Analytics and Intelligent Systems for Cyber Threat IntelligenceSuurem pilt
  • Formaat: Hardback, 280 pages, kõrgus x laius: 234x156 mm, kaal: 453 g, 44 Tables, black and white; 87 Illustrations, color; 7 Illustrations, black and white
  • Ilmumisaeg: 28-Apr-2023
  • Kirjastus: River Publishers
  • ISBN-10: 8770227780
  • ISBN-13: 9788770227780
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9788770227780.html
Märksõnad:

In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used.

This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications.

Technical topics discussed in the book include:
• Big data analytics for cyber threat intelligence and detection
• Artificial intelligence analytics techniques
• Real-time situational awareness
• Machine learning techniques for CTI
• Deep learning techniques for CTI
• Malware detection and prevention techniques
• Intrusion and cybersecurity threat detection and analysis
• Blockchain and machine learning techniques for CTI



This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security.

1. Introduction
2. Cyber Threat Intelligence Model: An Evaluation of Taxonomies and Sharing Platform within Cyber Threat Intelligence
3. Evaluation of Open Source Web Application Firewalls for Cyber Threat Intelligence
4. User Privacy Protection Mechanisms and Attacks Models in LBS: A Comprehensive Survey
5. Analysis of Encrypted Network Traffic using Machine Learning Models
6. Comparative Analysis of Android Application Dissection and Analysis Tools for Identifying Malware Attributes
7. Classifying Android Pending Intent Based Securities using Machine Learning Algorithms
8. Machine Learning and Blockchain Integration for Security Applications
9. Cyberthreat Real-time Detection Based on an Intelligent Hybrid Network Intrusion Detection System
10. Intelligent Malware Detection and Classification using a Boosted Tree Learning Paradigm
11. Malware and Ransomware Classification, Detection and Prevention Using Artificial Intelligence Techniques

Yassine Maleh, Imed Romdhani