Publication Type : Journal Article
Publisher : Advances in Big Data and Cloud Computing, Advances in Intelligent Systems and Computing
Source : Advances in Big Data and Cloud Computing, Advances in Intelligent Systems and Computing, Springer Verlag, Volume 645, Singapore, p.147-155 (2018)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045155327&doi=10.1007%2f978-981-10-7200-0_13&partnerID=40&md5=39a941c064a4b179f7bb3cfe68227717
Keywords : Android (operating system), Benign, Computer crime, Cryptographic activities, Droidbox, Dynamic features, Dynamics, Information leakage, malware, Network activities, Static, Static analysis, Static and dynamic analysis
Campus : Coimbatore
School : School of Engineering
Center : TIFAC CORE in Cyber Security
Department : Computer Science
Verified : Yes
Year : 2018
Abstract : In this work, we perform a comparitive study on the behavior of malware and benign applications using its static and dynamic features. In static analysis, the permissions required for an application are considered. But in dynamic, we use a tool called Droidbox. Droidbox is an android sandbox which can monitor some app actions like network activities, file system activities, cryptographic activities, information leakage, etc. Here, we consider these actions as well as dynamic API calls of applications. We propose to implement an android malware detector that can detect an app whether it is malware or not, prior to installation. © 2018, Springer Nature Singapore Pte Ltd.
Cite this Research Publication : K. Sugunan, Dr. Gireesh K. T., and Dhanya, K. A., “Static and Dynamic Analysis for Android Malware Detection”, Advances in Big Data and Cloud Computing, Advances in Intelligent Systems and Computing, vol. 645, pp. 147-155, 2018.