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An Intelligent Multi-Agent Based Detection Framework for Classification of Android Malware

机译:基于智能多功能代理的Android恶意软件分类的检测框架

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Android is currently the most popular operating system for smartphone devices with over 900 million installations until 2013. It is also the most vulnerable platform due to allowing of software downloads from 3rd party sites, loading additional code at runtime, and lack of frequent updates to known vulnerabilities. Securing such devices from malware that targets users is paramount. In this paper, we present a Jade agent based framework targeted towards protecting Android devices. We also focus on scenarios of use where such agents can be dynamically launched. We believe, a detection technique has to be intelligent due to limited battery constraints of these devices. Moreover, battery utilization might become secondary in certain settings where detection accuracy is given a higher preference. In this framework, the expensive analysis components utilizing machine-learning algorithms are pushed to server side, while agents on the Android client are used mainly for intelligent feature gathering.
机译:Android是目前最受欢迎的操作系统,用于智能手机设备,超过900万辆安装,直到2013年。它也是最脆弱的平台,因为允许来自第三方网站的软件下载,在运行时加载额外的代码,并且缺乏已知频繁更新漏洞。从恶意软件中保护此类设备,该设备针对用户是至关重要的。在本文中,我们展示了一个基于玉器的桥梁,旨在保护Android设备。我们还专注于使用这些代理可以动态启动的使用情况。我们认为,由于这些设备的电池限制有限,可以智能检测技术。此外,电池利用可能在某些设置中变为次要检测精度给出更高的偏好。在该框架中,利用机器学习算法的昂贵分析组件被推到服务器端,而Android客户端上的代理主要用于智能特征收集。

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