The Google Android platform supports provisioning of packaged applications to an Android device. However, an existing approach requires user's interaction during the installation of a new application or its modules. We present a new approach to dynamic modules loading which enables provisioning of new modules to Android device dynamically without the interaction with the user. It will allow complex applications to adapt to the surrounding conditions and requirements of the user by downloading additional code from a server or a neighboring peer device. In our solution we propose to replace the default application class-loader with a custom one while employing some existing mechanisms of class-loading from APK packages at the Android platform.
Android OS has a function with which an application can work in screen-off state without user's operation. In this paper, we propose a method for identifying applications which largely drain battery in Screen-off state in Android devices. We monitor the wake-up of Android devices and estimate the power consumption of each application based on the monitoring results. Our experimental results demonstrate that our method can identify power draining applications effectively.
The current detection approach is that the application store checks the application to be put on the shelf. The application store rejects it on the shelf if the Android application is determined to be a repackaged application. However, the Android system application distribution management is confusing, and some small application stores do not have the ability to scan all the repackaged applications. Even some application stores are inherently malicious. Therefore, this paper proposes an active Android application repacking detection approach. The active detection approach embeds the code watermarking with detection function in the application program, reinforces the application by itself, and resists the attacker’s repackaging attack. The effectiveness of proposed approach is verified by comparing application signatures and code watermarking signatures. Android Projects - Project Center in Kumbakonam
Scholars proposed many ways to identify repackaged Android applications, which mainly focus on static and dynamic analysis. Zhou et al. detect the repackaged applications according to the fingerprint similarity with those applications from the official Android Market. They generate app-specific fingerprint based on a fuzzy hashing technique. To improve detection speed and analyze a much larger application corpus, Hanna et al. proposed a scalable distributed similarity detection infrastructure based on feature hashing . However, the static analysis approaches have a high false positive rate.
In order to reduce the false positive rate, researchers began to use dynamic analysis methods to determine the Android code repackaging . Crussell et al. detected cloned Android applications based on program dependence graphs . Wang et al. identified software theft based on application birthmark that represents the unique character of the runtime behavior . Based on an observation that some critical runtime values are hard to be replaced or eliminated, Jhi et al. detected application plagiarism based on runtime values .
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