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http://dx.doi.org/10.13089/JKIISC.2016.26.5.1235

Relationship Analysis between Malware and Sybil for Android Apps Recommender System  

Oh, Hayoung (Ajou University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.26, no.5, 2016 , pp. 1235-1241 More about this Journal
Abstract
Personalized App recommendation system is recently famous since the number of various apps that can be used in smart phones that increases exponentially. However, the site users using google play site with malwares have experienced severe damages of privacy exposure and extortion as well as a simple damage of satisfaction descent at the same time. In addition, Sybil attack (Sybil) manipulating the score (rating) of each app with falmay also present because of the social networks development. Up until now, the sybil detection studies and malicious apps studies have been conducted independently. But it is important to determine finally the existence of intelligent attack with Sybil and malware simultaneously when we consider the intelligent attack types in real-time. Therefore, in this paper we experimentally evaluate the relationship between malware and sybils based on real cralwed dataset of goodlplay. Through the extensive evaluations, the correlation between malware and sybils is low for malware providers to hide themselves from Anti-Virus (AV).
Keywords
Recommendation system; Sybil; Android App; Crawling; Correlation;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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