A detailed analysis of the KDD CUP 99 data set
Open accessAbstract
During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks, and KDDCUP'99 is the mostly widely used data set for the evaluation of these systems. Having conducted a statistical analysis on this data set, we found two important issues which highly affects the performance of evaluated systems, and results in a very poor evaluation of anomaly detection approaches. To solve these issues, we have proposed a new data set, NSL-KDD, which consists of selected records of the complete KDD data set and does not suffer from any of mentioned shortcomings.
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In anomaly-based intrusion detection literature, the KDD'99 dataset is the dataset of choice in most works, and some have also used the improved NSL-KDD dataset released in 2009.
“A quick glance at Tables 22, 23, and 24 will reveal that the KDD'99 dataset is the dataset of choice in most anomaly-based intrusion detection literature, where some have also employed the improved version of the dataset, NSL-KDD [438] released in 2009.”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [438]
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Research works printed but not linked: 2
- KDD Cup 1999. Available on: http://kdd.ics.uci.edu/databases/kddcup 99/kddcup99.html, Ocotber 2007.
- "Nsl-kdd data set for network-based intrusion detection systems." Available on: http://nsl.cs.unb.ca/KDD/NSL-KDD.html, March 2009.
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- Authors
- Tavallaee, M., Bagheri, E., Lu, W., & Ghorbani, A. A.
- Affiliations
- University of New Brunswick (CA)
- Venue
- 2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications
- Publisher
- IEEE
- Published
- 2009-07
- Pages
- 1-6
- OpenAlex
- W2099940443
- Cited by
- 5,396
- References
- 21
- Citations by year
- 2026: 539 · 2025: 640 · 2024: 601 · 2023: 621 · 2022: 563 · 2021: 536 · 2020: 464 · 2019: 344 · 2018: 253 · 2017: 202 · 2016: 150 · 2015: 145 · 2014: 115 · 2013: 102 · 2012: 64
- FWCI
- 32.57
- Type
- conference paper
- Language
- en
- Open access
- Locations
- IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA) (publishedVersion)
- NPARC (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Engineering › Biomedical Engineering › Artificial Immune Systems Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Keywords
- KDD Cup 1999 dataset, anomaly detection, intrusion detection systems, network security, NSL-KDD dataset, novel attack detection
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