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Building a knowledge-based society is widely recognized as leading to human, social and economic benefits. This paper explores the issue of using knowledge management as an instrument for the development and sustainability of this knowledge society. The paper attempts to achieve its purpose through four main integrated steps: providing a brief review of knowledge management and the knowledge society; viewing knowledge management according to the STOPE “strategy, technology, organization, people and the environment” scope; incorporating knowledge management into the six-sigma DMAIC “define, measure, analyze, improve, and control” process; and deriving observations on the outcome, and producing guidelines for future work. The paper emphasizes the claim that developing and continuously sustaining the knowledge society can be achieved by applying knowledge management through building it into the STOPE scope and the six-sigma process, and by considering the multi-level nature of the society. The paper enjoys a high potential as a guide to knowledge management driven development and sustainability of the knowledge society at all levels. This would be beneficial to all those interested and concerned with supporting the role of knowledge in their own societies.

Network based intrusion causes predominantly to reveal network and service vulnerabilities. And that is why network based intrusion detection system execute thoroughly packet inspection. For faster execution with better detection accuracy, of the overall procedure while facing new dataset, we are representing a hybrid intrusion detection system in this paper. The hybridized algorithms are Triangle Inequality based k-means clustering algorithm and k-nearest neighbor classifier. Basically a combination of clustering and classification algorithms is studied in this paper. The dataset we used is the refined version of KDD'99 dataset and it is NSL KDD dataset. Some ingrained problems are solved in NSL KDD dataset. This paper work mainly focuses on the reduction of the false alarm rate. But the system is capable of detecting U2R, R2L, probe and Dos with high accuracy. Keywords Hybrid intrusion detection system, data mining, Triangle Inequality based k-means, k nearest neighbor, NSL-KDD dataset, accuracy, false alarm rate.