Flow Monitoring Explained: From Packet Capture to Data Analysis With NetFlow and IPFIX

By Rick Hofstede, Pavel Čeleda, Brian Trammell, Idilio Drago, Ramin Sadre, Anna Sperotto, Aiko Pras. IEEE Communications Surveys and Tutorials, 2014

449 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/8af09f463e05a66ad4880911e0d16498434c0121

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Athanasios V. Vasilakos
2. André Costa Drummond
3. Paulo Angelo Alves Resende

In Computer Networks and Communications

1. Sudip Misra
2. Athanasios V. Vasilakos
3. André Costa Drummond
4. Paulo Angelo Alves Resende
5. Samaresh Bera

Citations in the corpus

• Software-Defined Networking for Internet of Things: A Survey (2017, background): “Therefore, in contrast to the traditional network flow monitoring schemes (such as NetFlow [43] and sFlow [44]), global network can be monitored efficiently with SDN, while installing a suitable monitoring module.”
• A Survey of Random Forest Based Methods for Intrusion Detection Systems (2018, methodology): “Hota and Shrivas (2014) evaluated five classifiers over the NSL-KDD dataset using Information Gain for feature selection and k-fold cross-validation.”
• Towards the Deployment of Machine Learning Solutions in Network Traffic Classification: A Systematic Survey (2019, unknown): “The work in [72] presents a comprehensive procedure for flow extraction using NetFlow and IPFIX.”