Collusion Detection using Predictive Functions based on Android Applications

Aurangzeb Magsi, A. Soomro
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引用次数: 0

Abstract

Android is used by most of the population of the users. It is an attractive target for malicious application developers due to its open source nature. These malicious writers are developing new trends to steal sensitive information from the devices. A new trend is represented as collision attack in this manner. During this attack different apps communicate via Inter-Process Communication (IPC) for variety of purposes. In this paper, a dynamic approach is proposed for automatic collision detection between communication applications. The focus of the study is on the sharing of multiple type data. Moreover, to select application for analyzing is difficult task to perform and two predictive functions has been used in this manner. The evaluation was performed on a dataset of 800 android applications for analyzing the colluding couples. The developed methodology produces an accuracy of 97.2% during the experiments by the developed system.  
基于Android应用预测功能的合谋检测
大多数用户都在使用安卓系统。由于其开源特性,它是恶意应用程序开发人员的一个有吸引力的目标。这些恶意作者正在发展从设备中窃取敏感信息的新趋势。以这种方式将一种新的趋势表示为碰撞攻击。在这次攻击中,不同的应用程序通过进程间通信(IPC)进行通信,以达到各种目的。本文提出了一种用于通信应用程序之间自动冲突检测的动态方法。研究的重点是共享多种类型的数据。此外,选择用于分析的应用是难以执行的任务,并且已经以这种方式使用了两个预测函数。该评估是在800个安卓应用程序的数据集上进行的,用于分析串通夫妇。所开发的方法在所开发的系统的实验过程中产生了97.2%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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