A detailed analysis of the KDD CUP 99 data set

A detailed analysis of the KDD CUP 99 data set

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...

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Bibliographische Detailangaben
Hauptverfasser: Tavallaee, M., Bagheri, E., Wei Lu, Ghorbani, A.A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Application software
Computational intelligence
Computer aided manufacturing
Computer networks
Computer security
Data security
Intrusion detection
Learning systems
Statistical analysis
Testing
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Beschreibung
Zusammenfassung: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.
ISSN:2329-6267
DOI:10.1109/CISDA.2009.5356528