z-logo
open-access-imgOpen Access
Network Intrusion Detection using Layered Approach and Hidden Markov Model
Author(s) -
Archana I. Patil,
Girish Kumar Patnaik,
Ashish T. Bhole
Publication year - 2014
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/16278-6049
Subject(s) - computer science , intrusion detection system , hidden markov model , intrusion , markov chain , markov model , data mining , artificial intelligence , machine learning , geochemistry , geology
intrusion detection systems uses either anomaly based or signature based technique. Both of these techniques have some problems. In anomaly based intrusion detection, the strategy is to suspect an unusual activity and thereby to continue further investigation. This approach is particularly effective against novel attacks. Signature based intrusion detection system detects known attacks timely and efficiently. For this approach, it is important to know the attack. The proposed system introduces a hybrid of anomaly based and signature based technique. The proposed system uses layered approach to get the results faster. Each layer in the layered approach is independent to detect and block an attack. Four different layers Probe, U2R, R2L and DOS are assigned with different features. The proposed hybrid technique with Hidden Markov Model can give better results compared to signature based and anomaly based intrusion detection techniques alone.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom