Support Vector Machines for TCP traffic classification
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In traffic classification, establishing ground truth for application classes in the training dataset can be achieved using application signature pattern matching.
“For instance, in traffic classification, establishing ground truth for application classes in the training dataset can be achieved using application signature pattern matching [140].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [140]
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Robust Network Traffic Classification
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Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions
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A survey of AIOps methods for failure management
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- Authors
- Este, A., Gringoli, F., & Salgarelli, L.
- Affiliations
- University of Brescia (IT)
- Corresponding author
- Salgarelli, Luca
- ORCID
- Gringoli, Francesco
- Venue
- Computer Networks
- Publisher
- Elsevier BV
- Published
- 2009-09
- Volume
- 53
- Issue
- 14
- Pages
- 2476-2490
- ISSN
- 1389-1286 (ISSN-L)
- OpenAlex
- W1973668864
- Cited by
- 270
- References
- 24
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 9 · 2023: 10 · 2022: 11 · 2021: 15 · 2020: 26 · 2019: 19 · 2018: 23 · 2017: 18 · 2016: 26 · 2015: 22 · 2014: 23 · 2013: 20 · 2012: 16
- FWCI
- 15.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer Networks (publishedVersion)
- Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Keywords
- support vector machine, multi-class classification, hyperparameter optimization, limited training data, IP networks
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