基于传感器的android OS(操作系统)设备恶意软件检测应用

B. Rajalakshmi, N. Anusha
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引用次数: 2

摘要

随着Android操作系统手机使用量的增加,手机也受到恶意软件的影响。市场上有许多反恶意软件可以检测并从设备中删除这些恶意软件。但是一旦恶意软件改变了形式,这些反恶意软件就无法检测到。为了克服这个问题,我们提出了一种使用SVM(支持向量机)工具的技术,提高了恶意软件检测的强度。每次在手机中安装新的应用程序时,都会提取与该应用程序相关的权限特性和API (application Programming Interface)调用,并赋予权重。权重是根据它们的恶意性质分配的。如果总权重超过预定义的阈值,那么它将被视为恶意软件并向用户报告。这种方法也可以检测到,即使恶意软件改变了它的形式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensor based application for malware detection in android OS(Operating System) devices
With the increase of Android OS mobile's usage day-to-day, mobiles are getting affected with malware applications. Many antimalware's are available in the market to detect and remove these malwares from the device. But these antimalware's fails to detect the once the malware changes its form. To overcome this, we proposed a technique using SVM (Support Vector Machine) tool, which increases the malware detection strength. Each time when a new application is installed in the mobile, the permission features and API (Application Programming Interface) calls related to the application are extracted and weights are assigned to them. The weights are assigned based on their malicious nature. If the total weight exceeds the predefined threshold then it will considered as malware and reports to the user. This method can also detect even if the malware changes its form.
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