Software Intrusion Detection Evaluation System: A Cost-Based Evaluation of Intrusion Detection Capability
- 1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, USA
- 2 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, USA
- 3 Department of Electrical and Electronics Engineering, University of Lagos, Lagos, Nigeria
- 4 Modeling, Analysis and Simulation Center, Old Dominion University, Norfolk, USA
Abstract
In this paper, we consider a cost-based extension of intrusion detection capability ( C ID ). An objective metric motivated by information theory is presented and based on this formulation; a package for computing the intrusion detection capability of intrusion detection system (IDS), given certain input parameters is developed using Java. In order to determine the expected cost at each IDS operating point, the decision tree method of analysis is employed, and plots of expected cost and intrusion detection capability against false positive rate were generated. The point of intersection between the maximum intrusion detection capability and the expected cost is selected as the optimal operating point. Considering an IDS in the context of its intrinsic ability to detect intrusions at the least expected cost, findings revealed that the optimal operating point is the most suitable for the given IDS. The cost-based extension is used to select optimal operating point, calculate expected cost, and compare two actual intrusion detectors. The proposed cost-based extension of intrusion detection capability will be very useful to information technology (IT), telecommunication firms, and financial institutions, for making proper decisions in evaluating the suitability of an IDS for a specific operational environment.
- Cárdenas, A.A., Baras, J.S. and Seamon, K. (2006) A Framework for the Evaluation of Intrusion Detection Systems. Proceedings of 2006 IEEE Symposium on Security and Privacy, Berkeley, Oakland, CA, 21-24 May 2006, 15 p.
- Janakiraman, S. and Vasudevan, V. (2009) Aco Based Distributed Intrusion Detection System. JDCTA, 3, 66-72. https://doi.org/10.4156/jdcta.vol3.issue1.janakiraman
- Beg, S., Naru, U., Ashraf, M. and Mohsin, S. (2010) Feasibility of Intrusion Detection System with High Performance Computing: A Survey. International Journal for Advances in Computer Science, 1, 26-35.
- Sasikumar, R. and Manjula, D. (2011) A Distributed Intrusion Detection System Based on Mobile Agents with Fault Tolerance. European Journal of Scientific Research, 62, 48-55.
- Gu, G., Fogla, P., Dagon, D., Lee, W. and Skoric, B. (2006) Measuring Intrusion Detection Capability: An Information-Theoretic Approach. Proceedings of the 2006 ACM Symposium on Information, Computer and Communications Security, Taipei, 21-24 March 2006, 90-101.
- Eid, M.A., Artail, H., Kayssi, A.I. and Chehab, A. (2008) Lamaids: A Lightweight Adaptive Mobile Agent-Based Intrusion Detection System. International Journal of Network Security, 6, 145-157.
- Singh, M. and Pathak, S. (2012) Xb@nd Implementation for Intrusion Detection System. International Journal of Engineering Research and Technology, 1, 1-6.
- Singh, M. and Sodhi, S. (2007) Distributed Intrusion Detection Using Aglet Mobile Agent Technology. Proceedings of National Conference on Challenges and Opportunities in Information Technology (COIT-2007) RIMT-IET, Mandi Gobindgarh, March 2007, 148-153.
- Sallay, H., AlShalfan, K.A., et al. (2009) A Scalable Distributed IDS Architecture for High Speed Networks. International Journal of Computer Science and Network Security, 9, 9-16.
- Saravanan, A., Ahmed, M.I. and Bama, S.S. (2017) A Novel Approach for Intrusion Detection System in Distributed Networks Using Mobile Agents. Journal of Intelligent and Fuzzy Systems, 33, 1-11.
- Gandhi, M. and Srivatsa, S. (2008) Detecting and Preventing Attacks Using Network Intrusion Detection Systems. International Journal of Computer Science and Security, 2, 49-58.
- Dastjerdi, A.V. and Bakar, K.A. (2008) A Novel Hybrid Mobile Agent Based Distributed Intrusion Detection System. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2, 2903-2906.