Machine Learning Based Automotive Forensic Analysis for Mobile Applications Using Data Mining

MD. Hussain Khan, G. Pradeepini

Abstract


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.


Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v16.i2.pp350-354

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics