An Extensive Survey on Intrusion Detection- Past, Present, Future
Author:
Affiliation:
1. Department of Computer Science and Engineering, SET Jain University, Bangalore, India
2. Department of Computer Science and Engineering, Global Academy of Technology, Bangalore, India
Publisher
ACM Press
Reference54 articles.
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2. Yu-Shu Chen and Yi-Ming Chen. 2009. Combining incremental Hidden Markov Model and Adaboost algorithm for anomaly intrusion detection. In Proceedings of the ACM SIGKDD Workshop on CyberSecurity and Intelligence Informatics (CSI-KDD '09), Hsinchun Chen, Marc Dacier, Marie-Francine Moens, Gerhard Paass, and Christopher C. Yang (Eds.). ACM, New York, NY, USA, 3--9. DOI=http://dx.doi.org/10.1145/1599272.1599276
3. Wei-Chao Lin, Shih-Wen Ke, Chih-Fong Tsai, CANN: An intrusion detection system based on combining cluster centers and nearest neighbors, Knowledge-Based Systems, Volume 78, 2015, Pages 13-21, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2015.01.009.
4. Rawat, Sanjay & Pujari, Arun K & Gulati, V & Vemuri, Rao. (2006). Intrusion Detection using Text Processing Techniques with a Binary-Weighted Cosine Metric. Journal of Information Assurance & Security (JIAS). 1. 43-50.
5. Muamer N. Mohammad, Norrozila Sulaiman, Osama Abdulkarim Muhsin, A novel intrusion detection system by using intelligent data mining in weka environment, Procedia Computer Science, Volume 3, 2011, Pages 1237-1242, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2010.12.198.
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