The Android Malware Handbook: Using Manual Analysis and ML-Based Detection

This guide provides an in-depth exploration of Android malware, covering historical attacks, machine-learning techniques for detection, and adapting strategies for identifying different malware categories. It helps security professionals stay informed and improve their ability to protect Android devices from malicious threats.

Format: Paperback / softback
Length: 328 pages
Publication date: 07 November 2023
Publisher: No Starch Press,US

This comprehensive guide to Android malware delves into the current threats facing the world's most widely used operating system. After exploring the history of attacks seen in the wild since Android's inception, including several malware families previously absent from the literature, you will practice static and dynamic approaches to analyzing real malware specimens. You will examine the machine-learning techniques used to detect malicious apps, the types of classification models that defenders can employ, and the various features of malware specimens that can become input to these models. You will then adapt these machine-learning strategies to the identification of malware categories such as banking trojans, ransomware, and SMS fraud.

How historical Android malware can enhance your understanding of current threats

Manual identification and analysis of current Android malware using static and dynamic reverse-engineering tools

Machine-learning algorithms can analyze thousands of apps to detect malware at scale

Weight: 646g
Dimension: 235 x 182 x 23 (mm)
ISBN-13: 9781718503304