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

Abstract

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.