Anomaly Detection Using Gaussian Mixture Probability Model to Implement Intrusion Detection System
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Springer International Publishing
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http://link.springer.com/content/pdf/10.1007/978-3-030-29859-3_55
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3. Barkan, O., Averbuch, A.: Robust mixture models for anomaly detection. In: 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), September 2016, pp. 1–6. https://doi.org/10.1109/MLSP.2016.7738885
4. Breunig, M.M., Kriegel, H., Ng, R.T., Sander, J.: LOF: identifying density-based local outliers. In: Chen, W., Naughton, J.F., Bernstein, P.A. (eds.) Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, 16–18 May 2000, Dallas, Texas, USA, pp. 93–104. ACM (2000). https://doi.org/10.1145/342009.335388
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