A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach

  IJCTT-book-cover
 
International Journal of ComputerTrends and Technology (IJCTT)          
 
© 2014 by IJCTT Journal
Volume-7 Number-2                          
Year of Publication : 2014
Authors : Bhavna Dharamkar , Rajni Ranjan Singh
DOI :  10.14445/22312803/IJCTT-V7P106

citation

      Bhavna Dharamkar , Rajni Ranjan Singh. Article: A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach, International Journal of Computer Trends and Technology (IJCTT) 7(2):100-105, January 2014. Published by Seventh Sense Research Group.

Abstract-
      Cyber attack detection and classification is major challenge for web and network security. The increasing data traffic in network and web invites multiple cyber attack. The dynamic nature and large number of attribute of cyber data faced a problem of detection and prevention. In current research trend various method and framework are proposed by different authors. These framework and proposed method is based on data mining and neural network approach. Data mining offers various techniques such as clustering, classification, rule generation and temporal event mining; these techniques are very efficient for detection process of cyber attack. The application of neural network in cyber attack classification use as feature reduction technique. Feature reduction is very important task in cyber attack classification; because the cyber attack data consists of huge amount of features. This paper presents various method of cyber attack detection and classification technique based on data mining and neural network approach along with IDS evaluation criteria and dataset used for validated of IDS is also discussed here.

References
[1] Shailendra Singh, Sanjay Silakari “An Ensemble Approach for Cyber Attack Detection System: A Generic Framework” 14th ACIS, IEEE 2013. Pp 79-85.
[2] X. Li et al., “Smart Community: An Internet of Things Application,” IEEE Commun. Mag., vol. 49, no. 11, 2011, pp. 68–75.
[3] V. Bapuji, R. Naveen Kumar2,Dr. A. Govardhan, S.S.V.N. Sarma “Soft Computing and Artificial Intelligence Techniques for Intrusion Detection System” Vol 2, No.4, 2012, pp 24-33.
[4] Hoa Dinh Nguyen , Qi Cheng “An Efficient Feature Selection Method For Distributed Cyber Attack Detection and Classification” IEEE 2013. pp 1-6.
[5] Bimal Kumar Mishra,Hemraj Saini “Cyber Attack Classification using Game Theoretic Weighted Metrics Approach” World Applied Sciences Journal 7, 2009. Pp 206-215.
[6] Xu Li, Inria Lille, Xiaohui Liang, Xiaodong Lin, Haojin Zhu “Securing Smart Grid: Cyber Attacks,Countermeasures, and Challenges” IEEE Communications Magazine IEEE 2012. Pp 38-46.
[7] Haitao Du, Christopher Murphy, Jordan Bean, Shanchieh Jay Yang “Toward Unsupervised Classification of Non-uniform Cyber Attack Tracks” International Conference on Information Fusion 2009. Pp 1919-1925.
[8] Abhishek Jain And Ashwani Kumar Singh “Distributed Denial Of Service (Ddos) Attacks - Classification And Implications”journal of Information and Operations Management vol-3 2012. Pp 136– 140.
[9] Dewan Md. Farid, Nouria Harbi, Emna Bahri, Mohammad Zahidur Rahman, Chowdhury Mofizur Rahman “Attacks Classification in Adaptive Intrusion Detection using Decision Tree” World Academy of Science, Engineering and Technology, 2009. Pp 86-91.
[10] Chee-Wooi Ten, Govindarasu Manimaran “Cybersecurity for Critical Infrastructures:Attack and Defense Modeling “IEEE TRANSACTIONS ON SYSTEMS, vol-40 IEEE 2010. Pp 853-865.
[11] Mohammad A. Faysel , and Syed S. Haque “Towards Cyber Defense: Research in Intrusion Detection and Intrusion Prevention Systems” IJCSNS, vol-7 2010. Pp 316-325.
[12] Shailendra Singh, Sanjay Agrawal, Murtaza,A. Rizvi and Ramjeevan Singh Thakur “ Improved Support Vector Machine for Cyber Attack Detection” WCECS IEEE 2011. Pp 1-6.
[13] Real-time Misuse Detection Systems, Proceedings of the IEEE on Information, 2004.
[14 Vineet Richhariya , Dr. J.L.Rana ,Dr. R.C.Jain ,Dr. R.K.Pandey” Design of Trust Model For Efficient Cyber Attack Detection on Fuzzified Large Data using Data Mining techniques” IJRCCT Vol 2, Issue 3, 2013. Pp 126-132.
[15] S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, and D. Zerkle. GrIDS-a graph based intrusion detection system for large networks. In Proceedings of the 19th National Information Systems Security Conference, September 1996.
[16] Howard, J.D. “An Analysis of Security Incidents on the Internet” Doctoral Thesis. UMI UMI Order No. GAX98-02539, Carnegie Mellon University.1998.
[17] James P. Anderson, “Computer security threat monitoring and surveillance,” IEEE 2007. pp 255-261.
[18] Deepak Rathore and Anurag Jain “Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network” in International Journal of Advanced Computer Research Volume-2 Number-3 Issue-5 September-2012.

Keywords
cyber attack, data mining, neural network and KDDCUP99.