DocumentCode
237696
Title
Increasing performance Of intrusion detection system using neural network
Author
Kumar, Sudhakar ; Yadav, Ankesh
Author_Institution
Dept. of Electr. Eng., Nat. Inst. of Technol., Raipur, India
fYear
2014
fDate
8-10 May 2014
Firstpage
546
Lastpage
550
Abstract
Rapid growth in Internet and in parallel attacks, vulnerability and threats, has made intrusion detection systems very essential component in all parts of security infrastructure. Building IDS is not a new task, classical signature based IDS are used but they are unable to handle novel attacks. In this paper artificial neural network based intrusion detection is proposed for complete KDD cup 99 dataset. Performance of the proposed ANN based IDS system is evaluated and results shows high anomaly detection accuracy for the complete KDD cup 99 dataset as compared to existing techniques.
Keywords
neural nets; security of data; ANN based IDS system; Internet; artificial neural network based intrusion detection system; complete KDD cup 99 dataset; neural network; parallel attacks; security infrastructure; Accuracy; Artificial neural networks; Network topology; Probes; Servers; Spread spectrum communication; Topology; ANN; Intrusion Detection System; KDD99 dataset;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location
Ramanathapuram
Print_ISBN
978-1-4799-3913-8
Type
conf
DOI
10.1109/ICACCCT.2014.7019145
Filename
7019145
Link To Document