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@article{148112,
        author = {NISHA .R and DR. R. SUBHA and V. BALAMURUGAN},
        title = {Search Rank Fraud and Malware Detection in Google Play Application},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {12},
        pages = {413-419},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148112},
        abstract = { The survey of FairPlay and a novel system discovers and leverages traces left behind by fraudsters, to detect both malware and apps subjected to search rank fraud. FairPlay correlates review activities and uniquely combines detected review relations with linguistic and behavioral signals gleaned from Google Play app data in order to identify suspicious apps. Adversaries can have chances to launch attacks by gathering victim’s information continuously. This survey describe that an adversary can successfully infer a victim’s vertex identity and community identity by the knowledge of degrees within a time period. The survey also recommend to a new supervised clustering algorithm to find groups of data cluster. It directly incorporates the information of sample categories into the fraud clustering process.},
        keywords = {Graph Mining, Co-Review Mining, Clustering, FairPlay, Security, Clique detection. },
        month = {},
        }