1st Edition

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence

    310 Pages 87 Color & 7 B/W Illustrations
    by River Publishers

    310 Pages 87 Color & 7 B/W Illustrations
    by River Publishers

    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

    1 Cyber Threat Intelligence Model: An Evaluation of Taxonomies and Sharing Platforms
    Hassan Jalil Hadi, Muhammad Adeen Riaz, Zaheer Abbas, et al.

    2 Evaluation of Open-sourceWeb Application Firewalls for Cyber Threat Intelligence
    Oumaima Chakir, Yassine Sadqi, and Yassine Maleh

    3 Comprehensive Survey of Location Privacy and Proposed Effective Approach to Protecting the Privacy of LBS Users
    Ahmed Aloui, Samir Bourekkache, Okba Kazar, et al.

    4 Analysis of Encrypted Network Traffic using Machine Learning Models
    Aradhita Bhandari, Aswani Kumar Cherukuri, and Sumaiya Thaseen Ikram

    5 Comparative Analysis of Android Application Dissection and Analysis Tools for Identifying Malware Attributes
    Swapna Augustine Nikale and Seema Purohit

    6 Classifying Android PendingIntent Security using Machine Learning Algorithms
    Pradeep Kumar D. S. and Geetha S.

    7 Machine Learning and Blockchain Integration for Security Applications
    Aradhita Bhandari, Aswani Kumar Cherukuri, and Firuz Kamalov

    8 Cyberthreat Real-time Detection Based on an Intelligent Hybrid Network Intrusion Detection System
    Said Ouiazzane, Malika Addou, and Fatimazahra Barramou

    9 Intelligent Malware Detection and Classification using Boosted Tree Learning Paradigm
    S. Abijah Roseline and S. Geetha

    10 Malware and Ransomware Classification, Detection, and Prevention using Artificial Intelligence (AI) Techniques
    Md Jobair Hossain Faruk, Hossain Shahriar, Mohammad Masum, et al.

    11 Detecting High-quality GAN-generated Face Images using Neural Networks
    Ehsan Nowroozi and Yassine Mekdad

    12 Fault Tolerance of Network Routers using Machine Learning Techniques
    Harinahalli Lokesh Gururaj, Francesco Flammini, Beekanahalli Harish Swathi, et al.


    Yassine Maleh, Imed Romdhani