Название: Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
Автор: Yassine Maleh, Mamoun Alazab, Loai Tawalbeh
Издательство: River Publishers
Серия: River Publishers Series in Security and Digital Forensics
Год: 2023
Страниц: 310
Язык: английский
Формат: pdf (true)
Размер: 27.2 MB

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.

The Android operating system is one of the most popular mobile phone operating systems. Due to its popularity and open-source nature, Android is attracted to many malware developers. They use Android mobile applications as a medium to compromise the security of the user and device. Malware developers construct malicious applications responsible for information leak­ age, privilege escalation, and data theft. To identify and automate the task of Android malware detection, the malware attributes should be extracted from the Android applications. This paper describes and demonstrates the tools used for Android application dissection and an analysis of malware attributes in various Android application components. The malware information that could be obtained from the Android application package is also discussed. Among the several Android application dissections and malware attribute analysis tools, it is noted that Androguard was one of the most prominent tools due to its several advantages.

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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