Performance Comparison of Host based and Network based Anomaly Detection using Fuzzy Genetic Approach (FGA)
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - August Issue 2013 by IJCTT Journal|
|Volume-4 Issue-8 |
|Year of Publication : 2013|
|Authors :Harjinder Kaur, Nivit Gill|
Harjinder Kaur, Nivit Gill"Performance Comparison of Host based and Network based Anomaly Detection using Fuzzy Genetic Approach (FGA)"International Journal of Computer Trends and Technology (IJCTT),V4(8):2739-2746 August Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- Intrusion is a deliberate unauthorized access, attempt, misuse or damage to some valuable data. Intrusion Detection Systems (IDS) are used to detect and report the intrusions for the computer systems and for the computer networks. IDS analyses the data or traffic and classifies the behavior of the particular host and a network into the normal or the suspicious activity. This paper compares the performance of the host based and the network based intrusion detection systems implemented using the Fuzzy Genetic approach. System log files are used as the dataset for the host based intrusion detection (HIDS) and NSL-KDD dataset is used for the network based intrusion detection (NIDS). Simulation results reveal that HIDS detects the normal behavior as well as the anomalous behavior better than NIDS.
 K. Hanumantha Rao, G. Srinivas, Ankam Damodhar and M. Vikas Krishna, “Implementation of Anomaly Detection Technique Using Machine Learning Algorithms,” International Journal of Computer Science and Telecommunications, vol. 2, no. 3, 2011.
 Jiankun Hu, “Host-Based Anomaly Intrusion Detection,” Handbook of Information and Communication Security, Springer Berlin Heidelberg, pp. 235-255, 2010.
 Giovanni Vigna, Christopher Kruegel, ” Host Based Intrusion Detection,” Handbook of Information Security, H. Bigdoli , December 2005.
 Sanoop Mallissery, Jeewan Prabhu, and Raghavendra Ganiga, "Survey on Intrusion Detection Methods," in proc. of 3rd Int. Conf. on Advances in Recent Technologies in Communication and Computing, Bangalore, 2011, pp. 224-228.
 Asmaa Shaker Ashoor and Sharad Gore, "Intrusion Detection System: Case study," in International Conference on Advanced Materials Engineering, vol. 15, Singapore, 2011, pp. 6-9.
 V Jyothsna, V V Ramaprasad, and K Munivara Prasad, "A Review of Anomaly based Intrusion Detection Systemss," International Journal of Computer Applications, vol. 28, no. 7, pp. 26-35, August 2011.
 P Garcia Teodoro, J Diaz Verdejo, G Macia Fernandez, and E Vazquez, "Anomaly based network intrusion detection: Techniques, Systems and Challenges," International Jouirnal of Computers and Security, vol. 28, no. 1, pp. 18-28, February-March 2009.
 Bharanidharan Shanmugam and Norbrik Bashah Idris, "Hybrid Intrusion Detection Systems(HIDS) using Fuzzy Logic," in Intrusion Detection Systems, Dr. Pawel Skrobanek, Ed. Croatia, Europe: InTech, 2011, ch. 8, pp. 135-155.
 Om Prakash Shukla, Amit Bahekar, Jaya Vijayvergiya, “Effective Fault Diagnosis and Maintenance Optimization by Genetic Algorithm,” Research Expo International Multidisciplinary Research Journal, vol.2, no.2, pp. 20-25, 2012.
 Rajdeep Borgohain, "FuGeIDS: Fuzzy Genetic paradigms in Intrusion Detection Systems," International Journal of Advanced Networking and Applications, vol. 3, no. 6, pp. 1409-1415, 2012.
 Mathworks, Genetic Algorithm and Direct search toolbox For use with Matlab. Natick, United States: Mathworks Inc., version 1, 2004.
 J. T. Yao, S.L. Zhao, L.V. Saxton, “A study on fuzzy intrusion detection,” Proc. of SPIE Data Mining, Intrusion Detection, Information Assurance, And Data Networks Security, Orlando, Florida, USA , vol. 5812, pp. 23-30, 2005.
 Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu, and Ali A. Ghorbani, “A Detailed Analysis of the KDD CUP 99 Data Set,” proc. of IEEE sympo. On computational Intelligence in Security and Defence Applications, 2009.
 Radhika Goel, Anjali Sardana, and Ramesh C. Joshi, ”Parallel Misuse and Anomaly Detection Model,” International Journal of Network Security, vol.14, no.4, pp. 211-222, July 2012.
 Mostaque Md. Morshedur Hassan, "Current Studies on Intrusion Detection System, Genetic Algorithm and Fuzzy Logic," International Journal of Distributed and Parallel Systems (IJDPS), vol. 4, no. 2, pp. 35-47, March 2013.
 Harjinder Kaur and Nivit Gill, “Host based Anomaly Detection using Fuzzy Genetic Approach (FGA),” International Journal of Computer Applications (IJCA), vol. 74, no. 20, pp. 5-9, July 2013.
Keywords : Intrusion, host/network based intrusion detection, NSL-KDD dataset, fuzzy logic, genetic algorithms.