2022
DOI: 10.1155/2022/7972230
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Security Hardened and Privacy Preserved Android Malware Detection Using Fuzzy Hash of Reverse Engineered Source Code

Abstract: The risk of malware has increased drastically in recent years due to advances in the IT industry but it also increased the need for malware analysis and prevention. Hackers inject malicious code using awful applications. In this research, a framework is proposed to identify malicious Android applications based on repacked malicious code. The sensitive features of android applications are extracted using source code. These extracted features are compared with existing malware signatures to identify repacked mal… Show more

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Cited by 6 publications
(2 citation statements)
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References 27 publications
(57 reference statements)
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“…Figure 1, is a big picture of the system that will extract the Android APK file into a malware dataset, then the analysis process will be carried out on the features contained in the APK file. The resulting dataset is the result of reverse engineering using the Jadx module [23], [24], which is a tool from Reverse Engineering. Reverse Engineering is the process of converting APK files into source code form.…”
Section: The Proposed Methods (Extracting Apk Android Files)mentioning
confidence: 99%
“…Figure 1, is a big picture of the system that will extract the Android APK file into a malware dataset, then the analysis process will be carried out on the features contained in the APK file. The resulting dataset is the result of reverse engineering using the Jadx module [23], [24], which is a tool from Reverse Engineering. Reverse Engineering is the process of converting APK files into source code form.…”
Section: The Proposed Methods (Extracting Apk Android Files)mentioning
confidence: 99%
“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”
mentioning
confidence: 99%