PROJECT TITLE :

Negative Selection and Knuth Morris Pratt Algorithm for Anomaly Detection

ABSTRACT:

During this paper an algorithm for detecting anomalous behavior on laptop systems is proposed. The work relies on information from the behavior of licensed users who have performed various tasks on a pc system over 2 years. The study uses a dynamic data structure which will encode the current activities of users and their behaviors. The identification of the foremost and least frequent tasks, based mostly on the historical database of each user, provides a simple method of making one profile of behavior. With this profile, we tend to apply negative selection techniques to get a affordable computational size set of anomalous detectors. We tend to then apply the Knuth-Morris-Pratt algorithm for locating detectors of anomalies as indicators of fraudulent behavior. This procedure for detecting anomalous behavior has been tested on real information and also the results prove the effectiveness of the proposal and encourage further research to improve the existing detection system.