Packet and Flow Based Network Intrusion Dataset

Author:

Gogoi Prasanta,Bhuyan Monowar H.,Bhattacharyya D. K.,Kalita J. K.

Publisher

Springer Berlin Heidelberg

Reference14 articles.

1. Adetunmbi, A.O., Falaki, S.O., Adewale, O.S., Alese, B.K.: Network intrusion detection based on rough set and k-nearest neighbour. International Journal of Computing and ICT Research 2, 60–66 (2008)

2. Amini, M., Jalili, R., Shahriari, H.R.: Rt-unnid: A practical solution to real- time network-based intrusion detection using unsupervised neural networks. Computers & Security 25(6), 459–468 (2006)

3. Bhuyan, M.H., Bhattacharyya, D.K., Kalita, J.K.: NADO: network anomaly detection using outlier approach. In: Proceedings of the ACM International Conference on Communication, Computing & Security, New York, NY, USA, pp. 531–536 (2011)

4. Daniel, B., Julia, C., Sushil, J., Ningning, W.: Adam: a testbed for exploring the use of data mining in intrusion detection. SIGMOD Rec. 30(4), 15–24 (2001)

5. Gogoi, P., Borah, B., Bhattacharyya, D.K.: Anomaly detection analysis of intrusion data using supervised & unsupervised approach. Journal of Convergence Information Technology 5, 95–110 (2010)

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