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

fYear

2009

fDate

8-10 July 2009

Firstpage

1

Lastpage

6

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CISDA.2009.5356528

Filename

5356528