Written by machine-learning researchers and members of the Android Security team, this guide subtitled "Detection and Analysis by Human and Machine" tackles discovering and understanding the malware that targets the Android operating system. Qian Han et al provide a comprehensive introduction to detecting common threats facing the Android ecosystem today.

The book explores the history of Android malware in the wild since the operating system first launched and then shows how to practice static and dynamic approaches to analyzing real malware specimens, and examines machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models.

Author: Qian Han et al
Publisher: No Starch
Date: November 2023
Pages: 328
ISBN: 978-1718503304
Print: 171850330X
Kindle: B0BZGZ5X5F
Audience: Android developers
Level: Intermediate
Category: Security

Topics covered:

• Dive deep into the source code of real malware
• Explore the static, dynamic, and complex features you can extract from malware for analysis
• Master the machine learning algorithms useful for malware detection
• Survey the efficacy of machine learning techniques at detecting common Android malware categories

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