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Full-Text Articles in Information Security
Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah
Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.
This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …
Semeo: A Semantic Equivalence Analysis Framework For Obfuscated Android Applications, Zhen Hu
Semeo: A Semantic Equivalence Analysis Framework For Obfuscated Android Applications, Zhen Hu
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Software repackaging is a common approach for creating malware. In this approach, malware authors inject malicious payloads into legitimate applications; then, to ren- der security analysis more difficult, they obfuscate most or all of the code. This forces analysts to spend a large amount of effort filtering out benign obfuscated methods in order to locate potentially malicious methods for further analysis. If an effective mechanism for filtering out benign obfuscated methods were available, the number of methods that must be analyzed could be reduced, allowing analysts to be more productive. In this thesis, we introduce SEMEO, a highly effective and …
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 …