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• W777262422 abstract "The success of the Android OS in its user base as well as in its developer base can partly be attributed to its communication model, named Inter-Component Communication (ICC), which promotes the development of loosely-coupled applications. By dividing applications into components that can exchange data within a single application and across several applications, Android encourages software reuse, and thus reduces developer burden. Unfortunately, the ICC model, which provides a message passing mechanism for data exchange among components, can be misused by malicious apps to threaten user privacy. Indeed, researchers have shown that Android apps frequently send users private data outside the device without their prior consent. Those applications are said to leak private data [2]. However, there is still a lack of a comprehensive study on the characteristics of the usage of ICCs by Android malware. Typically, what is the extent of the presence of privacy leaks in Android malware? To answer such a question, an Android analysis tool has to be developed for tracking privacy leaks. Although, most of the privacy leaks are simple, i.e., easily identifiable as they operate within a single component. Thus, analyzing components separately is not enough to detect leaks: it is necessary to perform an inter-component analysis of applications. Android app analysts could leverage such a tool to identify malicious apps that leak private data. For the tool to be useful, it has to be highly precise and minimize the false positive rate when reporting applications leaking private data. Thus, we propose IccTA1 , an Inter-component communication Taint Analysis tool, for a sound and precise detection of ICC links and leaks. Although our approach is generic and can be used for any data-flow analysis, we focus in this paper on using IccTA to detect ICC-based privacy leaks. we test IccTA on 15,000 real-world apps randomly selected from Google Play market in which we detect 337 apps with 2,395 ICC leaks. We also launch IccTA on the MalGenome [5] set containing 1260 malware, where IccTA reports 108 apps with 534 ICC leaks. By comparing the detecting rate r = # of detected apps # of tested apps of the two data sets, we found that rMalGenome = 8.6% is much higher than rGoogleP lay = 2.2%. Thus, we can conclude that malware are using ICC to leak private data more than benign apps, making ICC a potential feature for malware 1 https://sites.google.com/site/icctawebpage/ detection. This paper is an extended abstract version of our research paper [3], where interested readers can find more details of this work." @default.
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• W777262422 date "2015-03-01" @default.
• W777262422 modified "2023-10-16" @default.
• W777262422 title "Using An Instrumentation based Approach to Detect Inter-Component Leaks in Android Apps" @default.
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