Cart (Loading....) | Create Account
Close category search window
 

An Anomaly Intrusion Detection Method Based on Shell Commands

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ye Du ; Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing ; Tong Wang

Intrusion detection has emerged as an important approach to security problems. This paper proposes an effective anomaly detection method based on Unix shell commands to learn patterns. By looking upon each short shell commands sequence as an instance and each observable symbol as a bag that contains some instances, the task of detecting abnormal behaviors can be mapped as multiple-instance learning. KNN algorithm and Euclidean distances are selected as learning approach and a new kernel method is proposed to calculate the deviation between normal and intrusive bags. The algorithm is simple and can be directly applied. Experiments demonstrate that the method can construct accurate and concise discriminator to detect intrusive actions.

Published in:

Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on

Date of Conference:

21-22 Dec. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.