A REVIEW ON KDD CUP99 AND NSL-KDD DATASET

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RITU BALA
Dr. Ritu Nagpal

Abstract

Abstract: Continues use of network services for information and resource sharing makes our work easier. But sometime the extensive use of network services leads many problems in the form of attacks or intrusions which demolish not only the privacy but also the integrity and accessibility of data. Detection of attacks or intrusions on the network is a serious issue of concern for the researchers. Intrusion Detection System solves the purpose of detecting intrusion on the network. Huge amount of data is required to simulate the powerful Intrusion Detection System (IDS) model as well as to train and testing the model. This paper, presents the review of datasets DARPA, KDDCup99 and NSL_KDD which are most widely used by researchers to detect the intrusion in computer network.

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References

L.Dhanabal, Dr. S.P. Shantharajah “A Study on NSL-KDD Dataset for Intrusion Detection system Based on Classification Algorithmsâ€, in International Journal of Advanced Research in Computer and Communication engineering, vol. 4, pp. 446-452, 2015.

Rung-Ching Chen, Kai-Fan Cheng and Chia-Fen Hsieh, “Using Rough Set and Support Vector Machine for Network Intrusion Detectionâ€, in International Journal of Network Security & Its Applications (IJNSA), vol 1, pp. 1-13 2009.

Al-Dhafian, B., Ahmad, I. & Al-Ghamid, A. “An Overview of the Current Classification Techniques†in International Conference on Security and Management, pp.82-88, 2015.

Alzobaidy, L. “Anomaly network intrusion detection system based on distributed time-delay neural network (DTDNN)â€, Journal of Engineering Science and Technology (JESTEC), vol.5, pp. 457-471, 2010.

Tavallaee, M.; Bagheri, E.; Wei Lu; and Ghorbani, A. “ A detailed analysis of the KDD CUP 99 data set†IEEE Symposium on Computational Intelligence in Security and Defense Applications (CISDA 2009), pp. 1-6, 2009.

Shaheen, A. “A comparative analysis of intelligent techniques for detecting anomalous internet trafficâ€, MSc. Thesis, King Fahd University, 2010.

Danijela D. Protić “Review of KDD Cup ‘99, NSL-KDD and Kyoto 2006+ Datasetsâ€, vol. 66, pp. 580-596, 2018.

Dr.K.Arunesh, M. Manoj Kumar, “A Comparative Study Of Classification Techniques For Intrusion Detection Using Nsl-Kdd Data Setsâ€, in International Conference on Recent Trends in Engineering Science, Humanity and Management, pp. 288-295, 2017.