The week's pick
Reseach Article
A Survey: Importance of ANN based NIDS in Detection of DoS Attacks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 83 - Number 11 |
| Year of Publication: 2013 |
| Authors: Sonali D. Tangi, M. D. Ingale |
10.5120/14494-2876
|
Sonali D. Tangi, M. D. Ingale . A Survey: Importance of ANN based NIDS in Detection of DoS Attacks. International Journal of Computer Applications. 83, 11 ( December 2013), 25-28. DOI=10.5120/14494-2876
Abstract
Today's world i. e. either private or public (government) sector totally influenced by Internet and networking for their business, entertainment purpose. But black side of an internet cannot be ignored . Internet makes the door open to the intruders and hackers. Any successful attempt made by intruders in capturing data causes a big loss of confidential data or digital money. This forces organizations to adopt serious security policy. It may include either use of an encryption methodology or firewall . Now a days as preventive security organization may use an Intrusion detection system. An Intrusion detection system classifies incoming data as normal data and attack data and if attack pattern is recognized it gives alarm to the network administrator . There are various algorithms and methods are proposed for IDS. In this paper we proposed the importance of ANN in developing NIDS for detecting denial of service attacks. The proposed ANN based NIDS will make classification of input packets into 4 categories DoS, U2R,R2L, PROBING in the first step . In the second step NIDS system can be enhanced to detect the DoS attack as Smruf, Teardrop, Neptune, Land, Pod, Back. This developed NIDS can minimize false positive and false negative rate by increasing number of hidden layers in the construction of ANN.
References
- Mohammad Reza Norouzian*, Sobhan Merati "Classifying Attacks in a Network Intrusion Detection System Based onArtificial Neural Networks", ISBN 978-89-5519-155-4, Feb. 13~16, 2011 ICACT2011
- Iftikhar Ahmad, Azween B Abdullah, Abdullah S Alghamdi, "Application of Artificial Neural Network in Detection of DOS Attacks"
- TaraporeN. Z. , Kulkarni D. B. and Kamakshi P. V. , "Application of artificial intelligence based techniques for intrusion Detection systems: a review", Journal of Artificial Intelligence ISSN: 2229-3965 & E-ISSN: 2229-3973, Volume 3, Issue 3, 2012, pp. -111-116.
- Dilip Kumar Barman, Dr. Guruprasad Khataniar, "design of intrusion detection system based on artificial neural network and application of rough set" , ISSN:2249-5789, International Journal of Computer Science & Communication Networks,Vol 2(4), 548-552
- Srinivas Mukkamala, Guadalupe Janoski, Andrew Sung,"Intrusion Detection: Support Vector Machines and Neural Networks "Department of Computer Science New Mexico Institute of Mining and Technology
- . Matti Manninen "Using Artificial Intelligence in Intrusion Detection Systems", Helsinki University of Technology.
- Mehdi Moradi and Mohammad Zulkernine "A Neural Network Based System for Intrusion Detection and Classification of Attacks".
- . Bhavin Shah , Bhushan H Trivedi , "Artificial Neural Network based Intrusion Detection System: A Survey", International Journal of Computer Applications (0975 – 8887) Volume 39– No. 6, February 2012.
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