Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Yingmei Wang
Beijing Graphics Institute

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Clustering and Hybrid Genetic Algorithm based Intrusion Detection Strategy Li Liu; Pengyuan Wan; Yingmei Wang; Songtao Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Ad hoc networks face serious security threat due to its inherent weaknesses. Intrusion detection is crucial technology in protecting the security of Ad hoc networks. Recently, Intrusion Detection Systems (IDS) face open issues, such as how to make use of intrusion detection technologies to excavate normal/abnormal behaviors from a lot of initialized data and dig out invasion models later for intrusion detection automatically and effectively. In this paper, we propose an enhanced algorithm combined improved clustering algorithm with Hybrid Genetic Algorithm (HGA), called Enhanced Intrusion Detection Algorithm (EIDA) for intrusion detection in Ad hoc networks. Clustering Algorithm is used to divide the normal/anomalous data from network and system behaviors. Then HGA is used to dig out the invasion rules. Our EIDA is an unsupervised anomaly detection algorithm. The experiment result shows that it is extensible and not sensitive to the sequence of the input data sets. It has the capacity to deal with different types of data and detection rate and false positive rate of intrusion detection has been improved effectively. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3353
Co-Authors Li Liu Pengyuan Wan Songtao Liu