A Scalable Solution Partially Supervised Approach for Generation of Family Signature against Android Malware
Clustering has been well studied for desktop malware analysis as an effective triage method. Malware could be malicious software that gets installed in your device and performs unwanted tasks. Mainly designed to transmit information about your web browsing habits to the third party Conventional similarity-based clustering techniques, however, cannot be immediately applied to Android malware analysis due to the excessive use of third-party libraries in Android application development and the widespread use of repackaging in malware development. Deceitful practices in Google Play, the most prominent Android application showcase, fuel look rank mishandle and malware multiplication. To distinguish malware, past work has concentrated on application executable and authorization examination. The proposed algorithm for a user should be given reviews to the app at one time again the user cannot be given to the review. After downloading mobile applications from Google play users are asked to give reviews about that particular downloaded applications. However fraudulent developers give fake ratings, about their application promote their application to the top. Hoax web algorithm [HWA] identified that for the detection of the ranking, rank, and review based evidence are considered.
Author Name: J. Ramya and K. Chandramohan
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College: Computer Science and Engineering, Gnanamani College of Technology, Pachal, Namakkal.
Keywords: Third-Party, Clustering Techniques, Fraud Application, Hoax web Algorithm.