Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
- 280 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
About this book
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
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Information
Table of contents
- Cover Page
- Half Title page
- Series page
- Title Page
- Copyright Page
- Contents
- Preface
- List of Figures
- List of Tables
- List of Contributors
- List of Abbreviations
- Introduction
- 1 Cyber Threat Intelligence Model: An Evaluation of Taxonomies and Sharing Platforms
- 2 Evaluation of Open-source Web Application Firewalls for Cyber Threat Intelligence
- 3 Comprehensive Survey of Location Privacy and Proposed Effective Approach to Protecting the Privacy of LBS Users*
- 4 Analysis of Encrypted Network Traffic using Machine Learning Models
- 5 Comparative Analysis of Android Application Dissection and Analysis Tools for Identifying Malware Attributes
- 6 Classifying Android PendingIntent Security using Machine Learning Algorithms
- 7 Machine Learning and Blockchain Integration for Security Applications
- 8 Cyberthreat Real-time Detection Based on an Intelligent Hybrid Network Intrusion Detection System
- 9 Intelligent Malware Detection and Classification using Boosted Tree Learning Paradigm
- 10 Malware and Ransomware Classification, Detection, and Prevention using Artificial Intelligence (Al) Techniques
- 11 Detecting High-quality GAN-generated Face Images using Neural Networks
- 12 Fault Tolerance of Network Routers using Machine Learning Techniques
- Index
- About the Editors