The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Flow Monitoring Explained: From Packet Capture to Data Analysis With NetFlow and IPFIX
Open accessAbstract
Flow monitoring has become a prevalent method for monitoring traffic in high-speed networks. By focusing on the analysis of flows, rather than individual packets, it is often said to be more scalable than traditional packet-based traffic analysis. Flow monitoring embraces the complete chain of packet observation, flow export using protocols such as NetFlow and IPFIX, data collection, and data analysis. In contrast to what is often assumed, all stages of flow monitoring are closely intertwined. Each of these stages therefore has to be thoroughly understood, before being able to perform sound flow measurements. Otherwise, flow data artifacts and data loss can be the consequence, potentially without being observed. This paper is the first of its kind to provide an integrated tutorial on all stages of a flow monitoring setup. As shown throughout this paper, flow monitoring has evolved from the early 1990s into a powerful tool, and additional functionality will certainly be added in the future. We show, for example, how the previously opposing approaches of deep packet inspection and flow monitoring have been united into novel monitoring approaches.
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Cites
McKeown (2008) · doi:10.1145/1355734.1355746 · Cited by 8,513
Stream Control Transmission Protocol
Stewart, R., Tüxen, M., & Nielsen, K. (2022) · doi:10.17487/rfc9260 · Cited by 1,922
Cisco Systems NetFlow Services Export Version 9
(2004) · doi:10.17487/rfc3954 · Cited by 954
Stream Control Transmission Protocol
(2007) · doi:10.17487/rfc4960 · Cited by 717
Network Innovation using OpenFlow: A Survey
Lara, A., Kolasani, A., & Ramamurthy, B. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.081313.00105 · Cited by 622
Extending Networking into the Virtualization Layer.
Pfaff, B., Pettit, J., Amidon, K., Casado, M., Koponen, T., & Shenker, S. J. (2009) · Cited by 510
An Overview of IP Flow-Based Intrusion Detection
Sperotto, A., Schaffrath, G., Sadre, R., Morariu, C., Pras, A., & Stiller, B. (2010) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2010.032210.00054 · Cited by 466
Self-citationEstan, C., Keys, K., Moore, D., & Varghese, G. (2004) · Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications · doi:10.1145/1015467.1015495 · Cited by 351
A parameterizable methodology for Internet traffic flow profiling
Claffy, K. C., Braun, H.-W., & Polyzos, G. C. (1995) · IEEE Journal on Selected Areas in Communications · doi:10.1109/49.464717 · Cited by 330
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Software-Defined Networking for Internet of Things: A Survey
Bera, S., Misra, S., & Vasilakos, A. V. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2746186 · Cited by 391
Machine Learning-Powered Encrypted Network Traffic Analysis: A Comprehensive Survey
Shen, M., Ye, K., Liu, X., Zhu, L., Kang, J., Yu, S., Li, Q., & Xu, K. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3208196 · Cited by 265
A Survey of Techniques for Mobile Service Encrypted Traffic Classification Using Deep Learning
Wang, P., Chen, X., Ye, F., & Sun, Z. (2019) · IEEE Access · doi:10.1109/access.2019.2912896 · Cited by 148
Challenges of future multimedia QoE monitoring for internet service providers
Robitza, W., Ahmad, A., Kara, P. A., Atzori, L., Martini, M. G., Raake, A., & Sun, L. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-017-4870-z · Cited by 57
SP-CIDS: Secure and Private Collaborative IDS for VANETs
Raja, G., Anbalagan, S., Vijayaraghavan, G., Theerthagiri, S., Suryanarayan, S. V., & Wu, X.-W. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3036071 · Cited by 53
Metadata
- Authors
- Hofstede, R., Čeleda, P., Trammell, B., Drago, I., Sadre, R., Sperotto, A., & Pras, A.
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2014
- Volume
- 16
- Issue
- 4
- Pages
- 2037-2064
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2053550965
- Cited by
- 431
- References
- 23
- FWCI
- 50.48
- Type
- journal article
- Language
- en
- Open access
- green
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