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Semi-supervised Multivariate Statistical Network Monitoring for Learning Security Threats
2019
IEEE Transactions on Information Forensics and Security
This paper presents a semi-supervised approach for intrusion detection. The method extends the unsupervised Multivariate Statistical Network Monitoring approach based on Principal Component Analysis by introducing a supervised optimization technique to learn the optimum scaling in the input data. It inherits the advantages of the unsupervised strategy, capable of uncovering new threats, with that of supervised strategies, able of learning the pattern of a targeted threat. The supervised
doi:10.1109/tifs.2019.2894358
fatcat:2a7oxvm6d5chvkxqkduvqahife