Abstract
Network utilization, monitoring, and fault isolation are important aspects of modern day network management. Recently introduced technologies such as software defined networks, Internet of Things, and network virtualization necessitate the tracking of various physical and virtual devices in the organization. In this work, we examine the popular network monitoring tool NetFlow. Its key components and operations are introduced. Case studies are presented to illustrate how data mining and machine learning techniques can be utilized to derive high-level information from NetFlow data, facilitating business and operational decision makings in organizations.
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References
CISCO: Introduction to Cisco IOS NetFlow, White Paper (2012) 1-16
Peddu, B.: ASR9K NetFlow White Paper. Cisco Support Community, https://supportforums.cisco.com/document/11933991/asr9k-netflow-white-paper [accessed: September 1, 2016]
Pandora FMS: Documentation NetFlow. http://wiki.pandorafms.com/index.php?title=Pandora:Documentation_en:Netflow[accessed: September 1, 2016]
Marchal, S., Jiang, X., State, R., Engel, T.: A Big Data Architecture for Large Scale Security Monitoring. IEEE International Congress on Big Data (2014) 56-63
Bodenham, D.A., Adams, N.M.: Continuous Monitoring of a Computer Network Using Multivariate Adaptive Estimation. IEEE 13th International Conference on Data Mining Workshops (2013) 311-318
Hsiao, H.-W., Chen, D.-N., Wu, T.J.: Detecting Hiding Malicious Website Using Network Traffic Mining Approach. 2nd International conference on Education Technology and Computer (2010) v5-276-280
Najafabadi, M.M., Khoshgoftaar, T.M., Calvert, C., Kemp C.: Detection of SSH Brute Force Attacks Using Aggregated Netflow Data. IEEE 14th International Conference on Machine Learning and Applications (2015) 283-288
Taylor, T., Paterson, D., Glanfield, J., Gates, C.: FloVis: Flow Visualization System. Cybersecurity Applications & Technology Conference for Homeland Security (2009) 186-198
Zhou, X., Petrovic, M., Eskridge, T., Carvalho, M., Tao, X.: Exploring Netflow Data Using Hadoop. ASE Big Data / Social Com / Cybersecurity Conference (2014) 1-10
Torres, L.M., Magafia, E., Izal, M., Morato, D.: Identifying Sessions to Websites as an Aggregation of Related Flows. XVth International Telecommunications Network Strategy and Planning Symposium (2012) 1-6
Caracas, A., Kind, A., Gantenbein, D., Fussenegger, S., Dechouniotis, D.: Mining Semantic Relations using NetFlow. 3rd IEEE/IFIP International Workshop on Businessdriven IT Management (2008) 110-111
CISCO: NetFlow gives Network Managers a Detailed View of Application Flows on the Network, Case Study (2003) 1-13
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Ratan, V., Li, K.F. (2017). NetFlow: Network Monitoring and Intelligence Gathering. In: Xhafa, F., Barolli, L., Amato, F. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2016. Lecture Notes on Data Engineering and Communications Technologies, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-49109-7_83
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DOI: https://doi.org/10.1007/978-3-319-49109-7_83
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