Thesis Intrusion Detection System

Thesis Intrusion Detection System-15
MINDS | Minnesota Intrusion Detection System, 2004. CS-2003-06, Department of Computer Science, Florida Institute of Technology, 2003 Ertoz, L., Eilertson, E., Lazarevic, A., Tan, P., Kumar, V., and Srivastava, J. Dinakara K, “Anomaly Based Network Intrusion Detection System”, Thesis Report, Dept. Dickerson, “Fuzzy network profiling for intrusion detection,” In Proceedings of the 19th International Conference of the North American Fuzzy Information Processing Society (NAFIPS), 13-15 July 2000, pp. Debar H, Becker M, and Siboni D, “A Neural Network Component for an Intrusion Detection System”, IEEE Computer Society Symposium on Research in Security and Privacy, Los Alamitos Oakland, CA, pp. DK Bhattacharyya and JK Kalita, 2014, “Network Anomaly Detection: A Machine Learning Perspective”, CRC Press, Taylor & Francis Group, International Standard Book Number-13: 978-1-4665-8209-5 Bhuyan, M.

MINDS | Minnesota Intrusion Detection System, 2004. CS-2003-06, Department of Computer Science, Florida Institute of Technology, 2003 Ertoz, L., Eilertson, E., Lazarevic, A., Tan, P., Kumar, V., and Srivastava, J. Dinakara K, “Anomaly Based Network Intrusion Detection System”, Thesis Report, Dept. Dickerson, “Fuzzy network profiling for intrusion detection,” In Proceedings of the 19th International Conference of the North American Fuzzy Information Processing Society (NAFIPS), 13-15 July 2000, pp. Debar H, Becker M, and Siboni D, “A Neural Network Component for an Intrusion Detection System”, IEEE Computer Society Symposium on Research in Security and Privacy, Los Alamitos Oakland, CA, pp. DK Bhattacharyya and JK Kalita, 2014, “Network Anomaly Detection: A Machine Learning Perspective”, CRC Press, Taylor & Francis Group, International Standard Book Number-13: 978-1-4665-8209-5 Bhuyan, M.

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263-268." Sampada Chavan, Khusbu Shah, Neha Dave and Sanghamitra Mukherjee” Adaptive Neuro-Fuzzy Intrusion Detection Systems” Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’04) IEEE 2004.

Detecting denial-of-service attacks with incomplete audit data. of the 14th Int'nl Conference on Computer Communications and Networks (ICCCN 2005) (October 2005), IEEE Computer Society, pp.

Ibitola Ayobami, “Strategic Sensor Placement for Intrusion Detection in Network-Based IDS” I. Intelligent Systems and Applications, 2014, 02, 61-68, I. Intelligent Systems and Applications, 2014, 02, 61-68 Vasilios S.; Fotini P., “Application of anomaly detection algorithms for detecting SYN flooding attacks”, Elsevier, Computer Communications, Vol. 1433, 1442, 2006 Dorothy D., “An Intrusion-Detection Model”, IEEE Transactions on Software Engineering, Vol.

1987 James C.; Jay H., “A Comparative Analysis of Current Intrusion Detection Technologies”, Proceeding of 4th Technology for Information Security Conference, TISC’96, Houston, TX, May.1996" Anurag Jain, Bhupendra Verma and J. Rana., “Anomaly Intrusion Detection Techniques: A Brief Review”, International Journal of Scientific & Engineering Research, Vol 5(7), 2014 Manasi Gyanchandani, J.

(2012) ‘Survey on data mining techniques to enhance intrusion detection’, International Conference on Computer Communication and Informatics, ICCI-2012, Coimbatore, India.

Intrusion Detection and Correlation: Challenges and Solutions. Supervisory control and data acquisition (SCADA) systems play an important role in our critical infrastructure (CI).Several of the protocols used in SCADA communication are old and lack of security mechanisms.This master thesis presents a SCADA Intrusion Detection System Test Framework that can be used to simulate SCADA traffic and detect malicious network activity.The framework uses a signature-based approach and utilize two different IDS engines, Suricata and Snort. Genetic Algorithms in Search, Optimization and Machine Learning. Protocol Anomaly Detection for Network-based Intrusion Detection, SANS Institute, GSEC Practical Assignment Version 1.2f, 2001 M. Given the exponential growth of Internet and increased availability of bandwidth, Intrusion Detection has become the critical component of Information Security and the importance of secure networks has tremendously increased. Though the concept of Intrusion Detection was introduced by James Anderson J. in the year 1980, it has gained lots of importance in the recent years because of the recent attacks on the IT infrastructure. AINT misbehaving – A taxonomy of anti-intrusion techniques. of 18th NIST-NCSC National Information Systems Security Conference, pages 163–172, 1995. Ilgun, Koral, USTAT:a real time IDS for Unix, Proceedings of the 1993 IEEE Computer Society Symposium on research insecurity and privacy, 1993. Valdes, Next-generation intrusion detection expert system (NIDES), Technical report, SRI-CSL-95-07, SRI International, Computer Science Lab, May 1995." Paxson, Vern, Bro: A system for detecting network intruders in real-time, Computer Network, v 31, n 23, Dec 1999. S, Jajodia S, Modelling requests among cooperating IDSs, Computer Communications, v 23, n 17, Nov, 2000." J. Denning, An Intrusion-Detection Model, IEEE Transactions on Software Engineering, vol. of Computer Science and Engineering, IIT Khargpur 2008 Guy Bruneau – GSEC Version 1.2f,” The History and Evolution of Intrusion Detection”, SANS Institute 2001.

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