UGR’16: A New Dataset for the Evaluation of Cyclostationarity-Based Network IDSs Macía Fernández, Gabriel Camacho Páez, José Magán Carrión, Roberto García Teodoro, Pedro Theron, Roberto Network security IDS Network traffic Netflow 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. 2019-04-01T06:17:30Z 2019-04-01T06:17:30Z 2018-03 info:eu-repo/semantics/article info:eu-repo/semantics/other http://hdl.handle.net/10481/55280 https://doi.org/10.1016/j.cose.2017.11.004 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España