000			02012nam a22002057a 4500
003			OSt
005			20220107122850.0
008			190618b xxu||||| |||| 00| 0 eng d
040			_cIIITMK
100			_aLadli Sultana (93617022) _915817
245			_aA static analysis based tool to detect vulnerabilities in android automotive applications
300			_aMSC CS 2017-2019
500			_aWith millions of Android device activation per day and billions of application installations from Google Play, Android is becoming one of the most widely used operating systems, even in automotives. Based on the Linux kernel, Android operating system is open and exible enough to run on dierent devices having varied hardware conguration. Modern smart car infotainment systems allow users to connect an Android device to the vehicle. The device then interacts with the hardware of the car, hence providing new interaction mechanisms to the driver. However this can be misused and become a major security breach into the car with subsequent security concerns : the Android device can both read sensitive data (speed, model, airbag status) and send dangerous commands (brake, lock, airbag explosion). Moreover, this scenario is unsettling since Android devices connect to the cloud, opening the door to remote attacks by malicious users of the cyberspace. The applications are bringing potential vulnerability when they access private information from the resources of the devices. In this project, I have developed a static analysis based tool to detect vulnerabilities in Android Automotive Applications. It mainly focuses on the presence of malicious content in the application by analysing permissions, API calls, etc. The acquired data is then classied using machine learning techniques.
502			_bMSC CS _c2017-2019 _dINT _eDr Tony Thomas
650			_aANDROID OPERATING SYSTEM _915818
650			_aSTATIC ANALYSIS _915819
650			_aVULNERABILITY _915820
650			_aMACHINE LEARNING _915821
942			_2ddc _cPR
999			_c6487 _d6487