2012 · 73 citations · 3 references
ComputingComputer ScienceCybersecurityApplication SecurityMalware AnalysisSoftware EngineeringCode Obfuscation AnalysisMalware ClassificationMalware Reverse EngineeringMobile Application Reverse EngineeringMobile Application VulnerabilitiesSoftware Vulnerability DiscoveryAndroid Application AnalysisAndroid Application VulnerabilitiesAndroid Malware AnalysisAnti-tampering DetectionCode Similarity AnalysisCode TamperingMalicious App DetectionTampering
As Android applications become increasingly ubiquitous, we need algorithms and tools to protect applications from product tampering and piracy, while facilitating valid product updates. Since it is easy to derive Java source code from Android byte code, Android applications are particularly vulnerable to tampering. This paper presents an algorithm, based on a customized similarity distance, which returns a value between 0 and 1, which can serve as a change indicator. Potential applications of the algorithm include 1) to determine if obfuscators, applied by developers, are protecting their code from piracy, 2) to determine if an Android application is infected with malware, facilitating the automatic extraction of the injected malware, and 3) to identify valid code updates and releases as part of the code release cycle.
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Rudi Cilibrasi, Paul Vitányi · IEEE Transactions on Information Theory · 2005 · 1.2K citations
Classification of malware using structured control flow
Silvio Cesare, Yang Xiang · 2010 · 110 citations
Programmer-friendly Decompiled Java
Nomair A. Naeem, Laurie Hendren · 2006 · 22 citations · Full text