Mitigation and risk factor analysis of android applications. (October 2018)

• Record Type: Journal Article
• Authors: Sharma, Kavita; Gupta, B.B.
• Is Part Of: Computers & electrical engineering. Volume 71(2018)
• Page Start: 416
• Page End: 430
• Publication Date: 2018-10
• Subjects: Android permission -- Data leakage -- Reverse engineering -- Malicious app classification -- Risk analysis -- Android app analysis; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.08.003
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Today, researchers face numerous challenges when attempting to identify malicious apps in the android market. Android apps require permissions to access the functionality of the mobile device. Moreover, these permissions can be used to know the app's behaviour. In this paper, we present a novel approach (called RNPDroid) for risk mitigation using the analysis of permissions. To evaluate the proposed approach, the M0Droid dataset is used, which consists of 400 Android app samples. All permissions of the obtained samples are analysed through reverse engineering, and total 165 permissions are attained. The computed value of F (517.3) is much higher than the tabulated value of F (2.61) at a 5% level of significance. The analysis of variance (ANOVA) states that one of the risk factors is significantly different from others. Moreover, the t -test is used to show the significant difference between medium and low risk.