Ugr'16: a new dataset for the evaluation of cyclostationarity-based network IDSs
-
Gabriel Maciá-Fernández; José Camacho; Roberto Magán-Carrión; Pedro García-Teodoro; Roberto Therón Sánchez
- Abstract:
- The evaluation of algorithms and techniques to implement intrusion detection systems heavily rely on the existence of well designed datasets. In the last years, a lot of efforts have been done towards building these datasets. Yet, there is still room to improve. In this paper, a comprehensive review of existing datasets is first done, making emphasis on their main shortcomings. Then, we present a new dataset that is built with real traffic and up-to-date attacks. The main advantage of this dataset over previous ones is its usefulness for evaluating IDSs that consider long-term evolution and traffic periodicity. Models that consider differences in daytime/night or weekdays/weekends can also be trained and evaluated with it. We discuss all the requirements for a modern IDS evaluation dataset and analyze how the one presented here meets the different needs.
- Research areas:
- Year:
- 2018
- Type of Publication:
- Article
- Keywords:
- dataset; IDS; network attacks; security
- Journal:
- Computer & Security
- Volume:
- 73
- Pages:
- 411-424
- Month:
- November
- ISSN:
- 0167-4048
- DOI:
- 10.1016/j.cose.2017.11.004
Hits: 4421