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 language | English |
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Title of host publication | 2015 IEEE Conference on Communications and NetworkSecurity, CNS 2015 |
Number of pages | 2 |
Publisher | IEEE Signal Processing Society |
Publication date | 3 Dec 2015 |
Pages | 739-740 |
Article number | 7346912 |
ISBN (Electronic) | 9781467378765 |
DOIs | |
Publication status | Published - 3 Dec 2015 |
Externally published | Yes |
Event | 3rd IEEE International Conference on Communications and Network Security, CNS 2015 - Florence, Italy Duration: 28 Sept 2015 → 30 Sept 2015 |
Conference
Conference | 3rd IEEE International Conference on Communications and Network Security, CNS 2015 |
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Country/Territory | Italy |
City | Florence |
Period | 28/09/2015 → 30/09/2015 |
Series | 2015 IEEE Conference on Communications and NetworkSecurity, CNS 2015 |
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Bibliographical note
Publisher Copyright:© 2015 IEEE.