PLSE Seminar Series - Alessandra Gorla - Mining Android Apps for Anomalous Behavior
Paul G. Allen School via YouTube
Overview
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Explore techniques for detecting suspicious behavior in Android apps and similar ecosystems in this 59-minute seminar by Alessandra Gorla. Learn about clustering apps based on advertised behavior extracted from natural language descriptions or graphical user interfaces. Discover methods to identify outliers within clusters by analyzing usage of sensitive Android APIs. Examine real-world examples of anomalies that highlight malicious behavior, such as weather apps sending messages or mismatched button functions. Gain insights into the challenges of program verification and the effectiveness of these detection techniques when applied to large sets of Android apps. Delve into topics including automatic workarounds, self-healing techniques, and information flow analysis. Understand the implications for malware detection and app security in mobile ecosystems.
Syllabus
Introduction
Background
The technique
Typical behavior
Common anomalies
Malware detection
Results
Information Flows Example
Example Twitter
Example Snapchat
Example Trick Wolf
The Idea
Evaluation
Conclusion
Questions
Taught by
Paul G. Allen School