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River Publishers Series in Digital Security and Forensics 

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence

Yassine Maleh, University Sultan Moulay Slimane, Morocco
Mamoun Alazab, Charles Darwin University, Australia
Loai Tawalbeh, Texas A&M University-San Antonio, USA
Imed Romdhani, Edinburgh Napier University, UK

ISBN: 9788770227780
e-ISBN: 9788770227773

Price: € 108.50

Available: April 2023



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 intelligence-based 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


Cyber threat intelligence, big data analytics, intelligent systems; machine learning, malwares detection, intrusion detection system, blockchain