Wake Lock Leak Detection in Android Apps Using Multi-Layer Perceptron

Muhammad Umair Khan,Shanza Abbas,Zhiqiang Wu,Scott Uk-Jin Lee

doi:10.3390/electronics10182211

Abstract

With the proliferation of mobile devices, the popularity of Android applications (apps) has increased exponentially. Efficient power consumption in a device is essential from the perspective of the user because users want their devices to work all day. Developers must properly utilize the application programming interfaces (APIs) provided by Android software development kit to optimize the power consumption of their app. Occasionally, developers fail to relinquish the resources required by their app, resulting in a resource leak. Wake lock APIs are used in apps to manage the power state of the Android smartphone, and they frequently consume more power than necessary if not used appropriately (also called energy leak). In this study, we use a multi-layer perceptron (MLP) to detect wake lock leaks in Android apps because the MLP can solve complex problems and determine similarities in graphs. To detect wake lock leaks, we extract the call graph as features from the APK and embed the instruction and neighbor information in the node’s label of the call graph. Then, the encoded data are input to an MLP model for training and testing. We demonstrate that our model can identify wake lock leaks in apps with 99% accuracy.

Highlights

We provide an overview of Android apps, an example of wake lock leak, multi-layer perceptron (MLP) and oversampling techniques.2.1
We provide an overview of Android apps, an example of wake lock leak, MLP and oversampling techniques
We evaluated our approach by performing different experiments and our results are presented

Summary

Introduction

We provide an overview of Android apps, an example of wake lock leak, MLP and oversampling techniques.2.1. We provide an overview of Android apps, an example of wake lock leak, MLP and oversampling techniques. Android apps are typically written in Java [36]. In 2011, a new programming language called Kotlin [37] was introduced and in 2017, Google announced support for Kotlin in the Android OS [38]. Kotlin was announced as the preferred language for Android app developers in 2019 by Google [39]. Android Native Development Kit [40] is a tool set that allows the implementation of a part of the app in native code using languages such as. The most popular Android app development environments are Android Studio (https://developer.android.com/studio, accessed on 15 July 2021) (which is the official Integrated Development Environment (IDE))

Objectives

Results

Conclusion