Malicious application detection in android — A systematic literature review

Abstract

Context:In last decade, due to tremendous usage of smart phones it seems that these gadgets became an essential necessity of day-to-day life. People are using new technologies and storing prominent data in their smartphones. Unfortunately, data related to privacy is center of attraction for attackers. Therefore, attackers are developing new techniques to steal the data from smartphones. Objective:The objective of study is to report a systematic literature review regarding malicious application detection in android operating system. Method:Standard systematic literature review method is used to carry out the research. In this, 380 research articles are studied which are published in various prominent international journals and conferences. Results:The different techniques which are used to investigate malicious application are identified. Furthermore, features used in static and dynamic technique are classified according to their usage in recent approaches. Various hybrid methods are analyzed and mapped according to the combination of static and dynamic features used. A variety of machine learning techniques are also identified and categorized in different classes. The datasets are listed are taken from various previous research approaches. Conclusion:This research will help to identify malicious applications in android operating system. New hybrid techniques must be implemented to investigate malware activities and recommendations are given for future research.