Written by machine-learning researchers and members of the Android
Security team, this all-star guide tackles the analysis and detection of
malware that targets the Android operating system.
This comprehensive guide to Android malware introduces current threats
facing the world's most widely used operating system. After exploring
the history of attacks seen in the wild since the time Android first
launched, including several malware families previously absent from the
literature, you'll practice static and dynamic approaches to analyzing
real malware specimens. Next, you'll examine the machine-learning
techniques used to detect malicious apps, the types of classification
models that defenders can use, and the various features of malware
specimens that can become input to these models. You'll then adapt these
machine-learning strategies to the identification of malware categories
like banking trojans, ransomware, and SMS fraud.
You'll learn:
- How historical Android malware can elevate your understanding of
current threats
- How to manually identify and analyze current Android malware using
static and dynamic reverse-engineering tools
- How machine-learning algorithms can analyze thousands of apps to
detect malware at scale
