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Analysis and Classification of Danger Level in Android Applications Using Naive Bayes Algorithm

机译:基于朴素贝叶斯算法的Android应用程序危险等级分析与分类

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This paper considers danger level classification of Android applications based on permissions and vulnerabilities by using Naive Bayes (NB) algorithm in order to assist and inform users whether an application is safe to use or not. With the increasing development and use of Android, unfortunately, malicious software (malware) and malicious applications are also beginning to increase. Many methods have been proposed to protect Android, however, they are only able to detect or classify Android applications against malware based on permission. This kind of approach is still considered less effective, because there is no information in classifying the danger level of an Android application, be it malware or goodware. To overcome the problem, this research classifies the danger level into three categories namely, safe, suspicious, and dangerous. The accuracy obtained from this research is 97.2%. To our knowledge, this is the first and only work to use danger level classification of Android applications based on permissions and vulnerabilities.
机译:本文通过使用朴素贝叶斯(NB)算法考虑了基于权限和漏洞的Android应用程序危险等级分类,以帮助并告知用户应用程序是否安全使用。不幸的是,随着Android的不断发展和使用,恶意软件(malware)和恶意应用程序也开始增加。已经提出了许多保护Android的方法,但是,它们只能基于权限检测恶意软件或对Android应用程序进行分类。仍然认为这种方法不太有效,因为在分类Android应用程序的危险级别(无论是恶意软件还是良好软件)方面没有任何信息。为了克服这个问题,本研究将危险等级分为三类,即安全,可疑和危险。从这项研究中获得的准确性为97.2%。据我们所知,这是基于权限和漏洞使用Android应用程序危险等级分类的第一个也是唯一的方法。

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