1. S. Chung, K. Kim, A heuristic approach to enhance the performance of intrusion detection system using machine learning algorithms, in Proceedings of the Korea Institutes of Information Security and Cryptology Conference (CISC-W’15) (2015)
2. N. Gao, L. Gao, Q. Gao, H. Wang, An intrusion detection model based on deep belief networks, in 2014 Second International Conference on Advanced Cloud and Big Data (CBD) (2014), pp. 247–252
3. D. Shin, K. Choi, S. Chune, H. Choi, Malicious traffic detection using K-means. J. Korean Inst. Commun. Inf. Sci. 41(2), 277–284 (2016)
4. S. Jo, H. Sung, B. Ahn, A comparative study on the performance of SVM and an artificial neural network in intrusion detection. J. Korea Acad.-Ind. Cooperation Soc. 17(2), 703–711 (2016)
5. P. Laskov, P. Dssel, C. Schfer, K. Rieck, Learning intrusion detection: supervised or unsupervised?’ in Proceedings of the 13th International Conference on Image Analysis and Processing (ICIAP), Cagliari, Italy, ed. by F. Roli, S. Vitulano (Springer, Berlin, 2005), pp. 50–57