ID2T: A DIY dataset creation toolkit for Intrusion Detection Systems

Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Nikolay Milanov, Christian Koch, David Hausheer, Max Muhlhauser

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

22 Citations (Scopus)

Abstract

Intrusion Detection Systems (IDSs) are an important defense tool against the sophisticated and ever-growing network attacks. These systems need to be evaluated against high quality datasets for correctly assessing their usefulness and comparing their performance. We present an Intrusion Detection Dataset Toolkit (ID2T) for the creation of labeled datasets containing user defined synthetic attacks. The architecture of the toolkit is provided for examination and the example of an injected attack, in real network traffic, is visualized and analyzed. We further discuss the ability of the toolkit of creating realistic synthetic attacks of high quality and low bias.

Original languageEnglish
Title of host publication2015 IEEE Conference on Communications and NetworkSecurity, CNS 2015
Number of pages2
PublisherIEEE Signal Processing Society
Publication date3 Dec 2015
Pages739-740
Article number7346912
ISBN (Electronic)9781467378765
DOIs
Publication statusPublished - 3 Dec 2015
Externally publishedYes
Event3rd IEEE International Conference on Communications and Network Security, CNS 2015 - Florence, Italy
Duration: 28 Sept 201530 Sept 2015

Conference

Conference3rd IEEE International Conference on Communications and Network Security, CNS 2015
Country/TerritoryItaly
CityFlorence
Period28/09/201530/09/2015
Series2015 IEEE Conference on Communications and NetworkSecurity, CNS 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Fingerprint

Dive into the research topics of 'ID2T: A DIY dataset creation toolkit for Intrusion Detection Systems'. Together they form a unique fingerprint.

Cite this