A detailed analysis of the KDD CUP 99 data set
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Abstract
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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The record
- Venue
- Topic
- Network Security and Intrusion Detection
- Field
- Computer Science
- Canadian institutions
- National Research Council CanadaUniversity of New Brunswick
- Funders
- —
- Keywords
- Computer scienceData miningAnomaly detectionSet (abstract data type)Data setSignature (topology)Anomaly (physics)Knowledge extractionArtificial intelligenceMathematics
- Has abstract in OpenAlex
- yes