Deep packet: a novel approach for encrypted traffic classification using deep learning
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- Authors
- Lotfollahi, M., Jafari Siavoshani, M., Shirali Hossein Zade, R., & Saberian, M.
- Affiliations
- Sharif University of Technology (IR)
- Venue
- Soft Computing
- Published
- 2019-05-13
- Volume
- 24
- Issue
- 3
- Pages
- 1999-2012
- ISSN
- 1432-7643 (ISSN-L)
- 1433-7479
- OpenAlex
- W2753434589
- Cited by
- 1,190
- References
- 8
- Citations by year
- 2026: 179 · 2025: 183 · 2024: 178 · 2023: 169 · 2022: 164 · 2021: 147 · 2020: 101 · 2019: 47 · 2018: 21 · 2017: 1
- FWCI
- 52.35
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Soft Computing (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Physical Sciences › Computer Science › Artificial Intelligence › Wireless Signal Modulation Classification
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- encrypted traffic classification, network traffic classification, application identification, stacked autoencoder, convolutional neural networks, deep packet inspection
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