2026-06-10T08:31:10Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4829 2021-12-13T06:50:05Z 1582963302567:1597824273898 user-ucsy

Android Malware Detection Framework Based on Static Analysis Soe, Yan Naung Oo, Khine Khine Mobile devices have gained tremendouspopularity over the last few years. The most popularusage is the smart phones. They are accepted andadmired by many mainly because they are capable ofproviding services such as banking, social network,etc all on the go. There are many operating systemsused in mobile devices. Among them, IOS andAndroid systems are the most acceptabletechnologies. Android platform is the fastest growingmarket in smart phone operating systems to date.Therefore, the malicious applications targeting theAndroid system has exploded in recent years. Theandroid malware detection framework is establishedby the static ways by analyzing the androidpermission and signature of source codes. Forsignature based detection, it is used clone detectiontechnique. For permission-based detection, it isdetected by using machine learning classifier. Bycombining with these two approach, this frameworkimproves the performance of the malware detection. 2017-02-16 http://hdl.handle.net/20.500.12678/0000004829 https://meral.edu.mm/records/4829