Masquerade Detection Using GUI Events in

Abstract— masquerade attack in computer systems refers to the illegitimate user activities while pretending to belegitimate user. detection of such attacks is done by discovering significant changes in user’s behavior based on hisprofile. profile is built by data produced from mouse, keyboard and other devices. in this paper we propose apractical approach for collecting gui data and deriving useful parameters included both mouse and keyboard eventsfrom windows os. we model user identification and masquerade detection as a binary classification problem.profiling and user classification is accomplished by use of support vector machine (svm) algorithm. feature vectorsare fed to svm. the output is behavioral pattern which builds the profile. system is trained by normal behavior anddetects deviations from profile. according to the results of implementation the proposed approach ensure detectionrate up to 94% with few false alarm.