Title :
A detailed analysis of the KDD CUP 99 data set
Author :
Tavallaee, Mahbod ; Bagheri, Ebrahim ; Lu, Wei ; Ghorbani, Ali A.
Author_Institution :
Fac. of Comput. Sci., Univ. of New Brunswick, Fredericton, NB, Canada
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.
Keywords :
security of data; statistical analysis; KDD CUP 99 data set analysis; anomaly detection; attack detection; signature-based intrusion detection system; statistical analysis; Application software; Computational intelligence; Computer aided manufacturing; Computer networks; Computer security; Data security; Intrusion detection; Learning systems; Statistical analysis; Testing;
Conference_Titel :
Computational Intelligence for Security and Defense Applications, 2009. CISDA 2009. IEEE Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-3763-4
Electronic_ISBN :
978-1-4244-3764-1
DOI :
10.1109/CISDA.2009.5356528
