Deep Learning for Encrypted Traffic Classification: An Overview
Deep Learning for Encrypted Traffic Classification: An Overview
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
Traffic classification has been studied for two decades and applied to a wide range of applications from QoS provisioning and billing in ISPs to security-related applications in firewalls and intrusion detection systems. Port-based, data packet inspection, and classical machine learning methods have been used extensively in the past, but their accu...
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Full title
Deep Learning for Encrypted Traffic Classification: An Overview
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TN_cdi_proquest_journals_2122920409
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2122920409
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.1810.07906
