2019 42nd International Conference on Telecommunications and Signal Processing (TSP) 2019
DOI: 10.1109/tsp.2019.8768885
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Accuracy of statistical machine learning methods in identifying client behavior patterns at network edge

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“…Deep packet inspection (DPI) [17,18] and deep flow inspection (DFI) [19] implement analysis on packets or flows through frequent item-mining and pattern-matching methods, but it is difficult to establish matching rules for encrypted traffic. The behavior detection method [20][21][22][23][24] achieves high identification accuracy of encrypted traffic only for some special applications or protocols. The methods based on statistical features currently show relatively good performance for encrypted traffic classification, and machine learning (ML) is the most popular and effective one among them.…”
Section: Related Workmentioning
confidence: 99%
“…Deep packet inspection (DPI) [17,18] and deep flow inspection (DFI) [19] implement analysis on packets or flows through frequent item-mining and pattern-matching methods, but it is difficult to establish matching rules for encrypted traffic. The behavior detection method [20][21][22][23][24] achieves high identification accuracy of encrypted traffic only for some special applications or protocols. The methods based on statistical features currently show relatively good performance for encrypted traffic classification, and machine learning (ML) is the most popular and effective one among them.…”
Section: Related Workmentioning
confidence: 99%