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In Advanced Computing and Intelligent Technologies (ICACIE), 2016 First International Conference on. A Novel algorithm for Network Anomaly Detection using Adaptive Machine Learning. (2010) Data Clustering Using K-Mean Algorithm For Network Intrusion Detection, Thesis, Lovely Professional University, Jalandhar.
Finally, this thesis studies load balancing and scheduling in cloud computing particularly when some of the workload is faulty or malicious.
The first original contribution proposes a hierarchical model for intrusion detection in the cloud environment.
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.
95-022, COAST Laboratory, Department of Computer Sciences, Purdue University, March 1994.
Mark Crosbie, Gene Spafford, Defending a Computer System using Autonomous Agents, Technical report No.
The algorithm was then extended to decentralized settings where servers maintain separate queues.
In this approach when a job arrives, a dispatching algorithm is used to decide which server to send it to.
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.