UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)
Top Cited Papers
- 1 November 2015
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
One of the major research challenges in this field is the unavailability of a comprehensive network based data set which can reflect modern network traffic scenarios, vast varieties of low footprint intrusions and depth structured information about the network traffic. Evaluating network intrusion detection systems research efforts, KDD98, KDDCUP99 and NSLKDD benchmark data sets were generated a decade ago. However, numerous current studies showed that for the current network threat environment, these data sets do not inclusively reflect network traffic and modern low footprint attacks. Countering the unavailability of network benchmark data set challenges, this paper examines a UNSW-NB15 data set creation. This data set has a hybrid of the real modern normal and the contemporary synthesized attack activities of the network traffic. Existing and novel methods are utilised to generate the features of the UNSWNB15 data set. This data set is available for research purposes and can be accessed from the link.Keywords
This publication has 8 references indexed in Scilit:
- Packet and Flow Based Network Intrusion DatasetCommunications in Computer and Information Science, 2012
- SSENet-2011: A Network Intrusion Detection System dataset and its comparison with KDD CUP 99 datasetPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- A detailed analysis of the KDD CUP 99 data setPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- A hybrid intrusion detection system design for computer network securityComputers and Electrical Engineering, 2009
- A New Data-Mining Based Approach for Network Intrusion DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Anomaly Based Network Intrusion Detection with Unsupervised Outlier DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- An Analysis of the 1999 DARPA/Lincoln Laboratory Evaluation Data for Network Anomaly DetectionLecture Notes in Computer Science, 2003
- Testing Intrusion detection systemsACM Transactions on Information and System Security, 2000