Open AccessMachine Learning Based Automotive Forensic Analysis for Mobile Applications Using Data Mining
Author(s) -
MD. Hussain Khan,
G. Pradeepini
Publication year - 2015
Publication title -
telkomnika: indonesian journal of electrical engineering/telkomnika
Language(s) - English
Resource type - Journals
eISSN - 2460-7673
pISSN - 2302-4046
DOI - 10.11591/tijee.v16i2.1623
Subject(s) - android (operating system) , computer science , mobile phone , cloud computing , automotive industry , computer security , phone , human–computer interaction , operating system , engineering , linguistics , philosophy , aerospace engineering
Phone is a device which provides communication between the people through voice, text, video etc. Now a day’s people may leave without food but not without using phones. No of operating systems are working with various versions and various security issues are working. Security is very important task in Mobiles and mobile apps. To improve the security status of mobiles, existing methodology is using cloud computing and data mining. Out traditional method is named as MobSafe to identify the mobile apps antagonism or graciousness. In the proposed system, we adopt Android Security Evaluation Framework (ASEF) and Static Android Analysis Framework (SAAF).In this paper, our proposed system works on machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.