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A Review On Network intrusion detection System Using Different Technique

Authors: Pragya Chhabra, Mrs. NishaBhati

Published in: IJRRETAS, Volume 4, Issue 5, pp. 1-4 (01 May 2018)

Impact Factor: 3.8 (2018)

License: CC BY 4.0 CC BY 4.0 (Open Access)

Certificate: View Certificate

Abstract

The computer network and internet networks are exposed to an increasing number of security threats. Intrusion Detection System plays a very important role in network security. Its main role in the network is to help computer system to create and deal with network attacks. For new types of attacks are emerging constantly, developing flexibility and adaptability safety-oriented approaches is a serious problem. In past few years, intrusion detection using data mining has captured the attention of researchers. Every researcher proposes a different algorithm for distinct categories. The increase speed of data flow information and also development in communication network along with many factors there is possibility of number of attacks on computer system. This paper provides us overview of intrusion detection system and various techniques used to implement intrusion detection system.

Keywords
  • Intrusion detection system (IDS)
  • Support Vector Machine
  • Artificial Neural
  • NSL-KDD
  • Security
  • Network analysis
  • etc
References
  1. Basant Subba , Santosh Biswas, Sushanta Karmakar, “A Neural Network Based System For Intrusion Detection And Attack Classification”, IEEE, 2016.
  2. Shi-Jinn Horng and Ming-Yang Su, “Novel Intrusion Detection System Based On Hierarchical Clustering and Support Vector Machines”, ELSEVIER, Expert Systems with Applications, 2011
  3. Sodiya A.S, Ojesanmi O.A, Akinola O.C, “Neural Network based Intrusion Detection Systems”, International Journal of Computer Applications, Volume 106 – No. 18, November 2014.
  4. Gisung Kim and Seungmin Lee, “A Novel Hybrid Intrusion Detection Method Integrating Anomaly Detection With Misuse Detection”, ELSEVIER, Expert Systems with Applications vol. 41 pp. 2014.
  5. F. Amiri, M. Yousefi, C. Lucas, A. Shakery and N. Yazdani, “Mutual Information-Based Feature Selection for Intrusion Detection Systems”, Journal of Network and Computer Applications, Vol. 34, 2011.
  6. Prof.Dighe Mohit S., Kharde Gayatri B., Mahadik Vrushali G., Gade Archana L., Bondre Namrata R, “Using Artificial Neural Network Classification and Invention of Intrusion in Network Intrusion Detection System”, International Journal of Innovative Research in Computer and Communication Engineering, .
  7. Juan Wang, Qiren Yang, Dasen Ren, “An intrusion detection algorithm based on decision tree technology”, In the Proc. of IEEE Asia-Pacific Conference on Information Processing, 2009.
  8. Surana S., “Intrusion Detection using Fuzzy Clustering and Artificial Neural Network, Advances in Neural Networks Fuzzy Systems and Artificial Intelligence”, ISBN- 978-960-474-379-7, 2013.
  9. Osoba O., Kosko B., “Noise-enhanced clustering and competitive learning algorithms, Neural Networks”, 2013.
  10. Lisehroodi M. M., Muda Z., and Yassin W., “A hybrid framework based on neural network MLP and Kmeans Clustering for Intrusion Detection System”, 4th International Conference on Computing and Informatics, 2013 .
  11. Sakthi M., Thanamani A. S., “An Enhanced K Means Clustering using Improved Hopfield Artificial Neural Network and Genetic Algorithm”, International Journal of Recent Technology and Engineering (IJRTE) Volume-2, Issue-3, 2013.
  12. Aneetha A.S., Bose S., “The Combined Approach for Anomaly Detection using Neural network and Clustering Techniques”, Computer Science & Engineering: An International Journal (CSEIJ), 2012.
How to Cite
APA: Chhabra, P., & NishaBhati (2018). A Review On Network intrusion detection System Using Different Technique. International Journal for Rapid Research in Engineering Technology & Applied Science, 4(5), 1–4. https://ijrretas.com/research-paper/a-review-on-network-intrusion-detection-system-using-different-technique
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Download Paper

Paper Id: IJRRETAS114

Publish Date: 2018-05-01

ISSN: 2455-4723

Publisher Name: ijrretas

About IJRRETAS

ijrretas is a leading open-access, peer-reviewed journal dedicated to advancing research in applied sciences and engineering. We provide a global platform for researchers to disseminate innovative findings and technological breakthroughs.

ISSN
2455-4723
Established
2015

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