Identification of Mobile Malicious Application using KAYO Technique

Abstract

Versatile explicit website pages contrast fundamentally from their work area partners in substance, format and usefulness. As needs be, existing systems to distinguish vindictive sites are probably not going to work for such website pages. In this paper, we structure and actualize kAYO,a system that recognizes malignant and kind versatile site pages. kAYO makes this assurance dependent on static highlights of a website page going from the quantity of iframes to the nearness of realized fake telephone numbers. In the first place, we tentatively exhibit the requirement for versatile explicit procedures and afterward recognize a scope of new static highlights that profoundly relate with portable malignant website pages. We at that point apply kAYO to a dataset of more than 350,000 known favorable and noxious versatile website pages and exhibit 90% precision in characterization. Besides, we find, portray and report various website pages missed by Google Safe Browsing and Virus Total, however identified by kAYO. At long last, we construct a program augmentation utilizing kAYO to shield clients from malignant portable sites progressively. In doing as such, we give the primary static investigation method to identify pernicious versatile site pages.