Android Malware Detection with Dynamic User Intention Based Analysis
Date Issued
2014
Date
2014
Author(s)
Teng, Yu-Chi
Abstract
Data leakage problem of Android apps is becoming more and more severe. Due to the enlarging Android ecology and the emerging of booming of various bytes of Android malwares, it is hard to keep user’s important data safe. For a malware, to steal important data from user is easy. The attacker can write an app and retrieve the user or device information from Android framework. Users with these apps installed is hard to know whether the application is using his or her data in an authorized way. In this paper, we provide a methodology to analyze out-going data with the observation of user-application interactions. With observation, we can get some information about the behavior of the app. Then we identify whether the app is benign or malicious by judging if an app is treating user’s data in a proper way. In brief, we want to tell if an app is treating user’s data in a right way by judging how the user interacts with the app. In the end, we show how this method performs by testing a numbers of applications, which are classified into two sets, normal set and malicious set respectively. With the evaluation of our method, we illustrate the performance of our system and its limitation.
Subjects
Android
安全
惡意程式
自動化測試
智慧型手機
資訊洩漏
隱私
Type
thesis
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