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Introduction
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Background
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The technique
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Typical behavior
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Common anomalies
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Malware detection
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Results
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Information Flows Example
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Example Twitter
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Example Snapchat
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Example Trick Wolf
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The Idea
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Evaluation
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Conclusion
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Questions
Description:
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.

PLSE Seminar Series - Alessandra Gorla - Mining Android Apps for Anomalous Behavior

Paul G. Allen School
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