Improving Leakage Path Coverage in Android Apps

G. Modi, V. Laxmi, Smita Naval, M. Gaur
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Abstract

With the phenomenal increase in Android apps usage and storing of personal information on mobile devices, securing this sensitive information has assumed significance. The Android application developers knowingly or unknowingly create apps that may directly or indirectly leak this information to outside world. The majority of state-of-the-art approachesdetect leaks through inter-component communication (ICC) within an app. Android allows inter-component communication (ICC) within the components of the same application or across multiple applications. ICC mechanism is used for the exchange of information among apps. Via ICC, an app or a set of apps can send the sensitive information out of the application or device.In this paper, we propose an approach for intra-app as well as inter-app data transfer analysis through intents and/or sharedpreferences that improve the coverage of leakage paths detectedas compared to existing approaches. Our proposed approach iscapable of analyzing more than two applications at a time. Wehave evaluated proposed approach on the DroidBench datasetand 116 real-time apps randomly selected and downloadedfrom Google PlayStore. We detected 1298 inter-component pathswithin an app and 215 inter-app sensitive paths. Our approachreported ~17.71% of more inter-component paths using sharedpreferences for data transfer.
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改进Android应用程序的泄漏路径覆盖率
随着Android应用程序的使用和个人信息在移动设备上的存储的显著增加,保护这些敏感信息具有重要意义。Android应用程序开发人员有意或无意地开发的应用程序可能直接或间接地将这些信息泄露给外部世界。大多数最先进的方法都是通过应用程序内的组件间通信(ICC)来检测泄漏。Android允许在同一应用程序或多个应用程序的组件内进行组件间通信(ICC)。ICC机制用于应用程序之间的信息交换。通过ICC,一个应用程序或一组应用程序可以将敏感信息发送出应用程序或设备。在本文中,我们提出了一种通过意图和/或共享偏好进行应用内部和应用间数据传输分析的方法,与现有方法相比,该方法提高了检测到的泄漏路径的覆盖范围。我们提出的方法不能同时分析两个以上的应用程序。我们在DroidBench数据集和116个随机选择并从Google PlayStore下载的实时应用程序上评估了提议的方法。我们在一个应用中检测到1298个组件间路径和215个应用间敏感路径。我们的方法报告了约17.71%的组件间路径使用共享偏好进行数据传输。
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