Malware Attacks on Smartphones and Their Classification Based Detection

Smart phones nowadays, with colossally large number of users have become very prominent[1]. Furthermore, this increasing prominence goes arm in arm with the rising number of malwares[2], thus making it inevitable to take cognizance of the need for an efficient malware detection mechanism. However, sundry former associated works like [3] & [4] for malware detection, have not cited a novel strategy which we feel can be attributed to the lack of malware classification in them. Fundamentally, classification of malwares provides a head start to the detection mechanism by curtailing the search space & the processing time of the detection mechanism. So in order to accomplish the malware classification, we develop few malwares and discuss their behavior and aftereffects on the device. And then we utilize the resource victimized by these malware on the phone as base for classification and allocate same class to those malwares that affect same resource. Finally by employing the aforementioned malware classification, we outline a strategy for their detection. Experimentation of the detection scheme on the malwares with and without classification reveals that with classification the real and CPU time consumed by detection process are almost 45% and 22% of the respective times without classification, which thus elucidates the fact that classification based malware detection in future can be employed as a propitious tool.