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Significant Permission Identification For Android Malware Detection, Lichao Sun
Significant Permission Identification For Android Malware Detection, Lichao Sun
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
A recent report indicates that a newly developed malicious app for Android is introduced every 11 seconds. To combat this alarming rate of malware creation, we need a scalable malware detection approach that is effective and efficient. In this thesis, we introduce SigPID, a malware detection system based on permission analysis to cope with the rapid increase in the number of Android malware. Instead of analyzing all 135 Android permissions, our approach applies 3-level pruning by mining the permission data to identify only significant permissions that can be effective in distinguishing benign and malicious apps. Based on the identified significant …
Efspredictor: Predicting Configuration Bugs With Ensemble Feature Selection, Bowen Xu, David Lo, Xin Xia, Ashish Sureka, Shanping Li
Efspredictor: Predicting Configuration Bugs With Ensemble Feature Selection, Bowen Xu, David Lo, Xin Xia, Ashish Sureka, Shanping Li
Research Collection School Of Computing and Information Systems
The configuration of a system determines the system behavior and wrong configuration settings can adversely impact system's availability, performance, and correctness. We refer to these wrong configuration settings as configuration bugs. The importance of configuration bugs has prompted many researchers to study it, and past studies can be grouped into three categories: detection, localization, and fixing of configuration bugs. In the work, we focus on the detection of configuration bugs, in particular, we follow the line-of-work that tries to predict if a bug report is caused by a wrong configuration setting. Automatically prediction of whether a bug is a configuration …