A Hybrid Approach for an Interpretable and Explainable Intrusion Detection System

Author:

Dias TiagoORCID,Oliveira NunoORCID,Sousa NorbertoORCID,Praça IsabelORCID,Sousa OrlandoORCID

Publisher

Springer International Publishing

Reference28 articles.

1. Institute Director, M., Cilluffo, F.J.: Cyber and Physical Security: Perspectives from the C-Suite Survey Research Project Conducted by the Center for Cyber and Homeland Security (CCHS) in Partnership with the International Security Management Association (ISMA) Project Leadership, May 2019. http://cchs.auburn.edu/_files/isma-survey-paper.pdf. Accessed 19 Apr 2021

2. Cole, E.: Network Security Bible, 2nd edn. Wiley, New York (2002)

3. KishorWagh, S., Pachghare, V.K., Kolhe, S.R.: Survey on intrusion detection system using machine learning techniques. Int. J. Comput. Appl. 78(16), 30–37 (2013). https://doi.org/10.5120/13608-1412

4. Snort - Network Intrusion Detection and Prevention System. https://www.snort.org/. Accessed 05 May 2021

5. Suricata | Open Source IDS/IPS/NSM Engine. https://suricata-ids.org/. Accessed 05 May 2021

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