MALWARE DETECTION: DEVELOPING A SYSTEM ENGINEERED FAIR PLAY FOR ENHANCING THE EFFICACY OF STEMMING SEARCH RANK FRAUD

Sidharth Grover
DPS R.K. Puram, New Delhi, India , IN

Keywords: Google Play, Android app market, fuel search rank abuse, malware proliferation, FairPlay, and online kernel classifier

Abstract

Nowadays Google Play have become mainly trendy Android app market, fuel search rank abuse and malware proliferation. The preceding works have paid attention to app assassinate as well as authorization study for identifying malware. To perceive together malware as well as apps subjected towards search rank fraud, we proposed a theory called FairPlay, a narrative scheme which determines as well as by using our influence; we can trace the fraudsters who are there at the back. To recognize apprehensive apps, FairPlay shows a relationship evaluation tricks as well as distinctively merge distinguish appraisal kindred in the midst of linguistic as well as behavioural indicator gleaned as of Google Play app data (87 K apps, 2.9 M appraise, and 2.4M reviewer, serene more than a semi year). By categorizing gold regular datasets of malware, fake as well as legal apps, FairPlay attains more than 95% accurateness. In search rank fraud, 75% of the well-known malware apps have been engaged which is shown by our proposed system. FairPlay determines hundreds of deceptive apps to facilitate at present escape Google Bouncer’s exposure knowledge. Furthermore, FairPlay
aids the innovation of additionally 1,000 analyses, the description intended for 193 apps, which disclose. Hence, Fairplay merely is of assistance evaluating as well as information apps. To classify the fraudulent apps in the function, we additionally proposed online kernel classifier.

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