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A Survey on Malware Detection Approaches Using EULA Analysis with Text Mining

机译:使用EULA分析和文本挖掘的恶意软件检测方法的调查

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Malware is a major threat to the computer security. There are so many variants of malware evolving each day which results the loss in economy as well as data and personal information is precious than economy. Malware prevention can be achieved by carefully analyzing the content of the EULA. As EULA analysis deals with analyzing the unstructured text documents, text mining concept plays an important role. This paper analyzes the detection mechanism for malware detection, using text mining over an ample set of existing EULA. The comparison presented in this paper highlights some malware analysis and text mining techniques. Although there are several malware detection systems exist, evolution and revolution is required to fill the gap in malware evolution and detection. In order to achieve the goal or to verify the authenticity of an executable, this paper provides an alternate approach to detect the malware before execution. EULA analysis which acts as gateway can be included in other behavioral or data mining based malware detection system to achieve both external and internal security of the computing system including mobile devices.
机译:恶意软件是对计算机安全性的主要威胁。每天都有不断演变的恶意软件变种,导致经济损失,而且数据和个人信息比经济珍贵。通过仔细分析EULA的内容可以防止恶意软件。由于EULA分析涉及分析非结构化文本文档,因此文本挖掘概念起着重要作用。本文通过在大量现有EULA上使用文本挖掘来分析恶意软件检测的检测机制。本文提供的比较重点介绍了一些恶意软件分析和文本挖掘技术。尽管存在几种恶意软件检测系统,但仍需要进化和革新来填补恶意软件进化和检测方面的空白。为了实现目标或验证可执行文件的真实性,本文提供了另一种在执行之前检测恶意软件的方法。可以将充当网关的EULA分析包含在其他基于行为或数据挖掘的恶意软件检测系统中,以实现包括移动设备在内的计算系统的外部和内部安全。

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