Abstract
We discuss the capability of a new feature set for malware detection based on potential component leaks (PCLs). PCLs are defined as sensitive data-flows that involve Android inter-component communications. We show that PCLs are common in Android apps and that malicious applications indeed manipulate significantly more PCLs than benign apps. Then, we evaluate a machine learning-based approach relying on PCLs. Experimental validations show high performance for identifying malware, demonstrating that PCLs can be used for discriminating malicious apps from benign apps.
Original language | English |
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Title of host publication | Proceedings - 2015 IEEE International Conference on Software Quality, Reliability and Security, QRS 2015 |
Editors | Jian Zhang, Bhavani Thuraisingham |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 195-200 |
Number of pages | 6 |
ISBN (Electronic) | 9781467379892, 9781467379885 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | IEEE International Conference on Software Quality, Reliability and Security 2015 - Vancouver, Canada Duration: 3 Aug 2015 → 5 Aug 2015 https://paris.utdallas.edu/qrs15/ |
Conference
Conference | IEEE International Conference on Software Quality, Reliability and Security 2015 |
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Abbreviated title | QRS 2015 |
Country/Territory | Canada |
City | Vancouver |
Period | 3/08/15 → 5/08/15 |
Internet address |