Bayesian Networks for Online Cybersecurity Threat Detection

Author:

Pappaterra Mauro José,Flammini Francesco

Publisher

Springer International Publishing

Reference17 articles.

1. IEEE, Syntegrity (2017) Artificial intelligence and machine learning applied to cybersecurity, presented in Washington DC, USA, 6th–8th October 2017, [Online]. Available at https://www.ieee.org/content/dam/ieeeorg/ieee/web/org/about/industry/ieee_confluence_report.pdf?utm_source=lp-linktext&utm_medium=industry&utm_campaign=confluence-paper. Accessed 20 Mar 2018

2. Pappaterra MJ, Flammini F (2019) A review of intelligent cybersecurity with Bayesian Networks. In: 2019 IEEE international conference on systems, man and cybernetics (SMC), Bari, Italy, pp 445–452

3. Shackleford D (2016) SANS 2016 Security Analytics Survey, SANS Institute. [Online]. Available at https://www.sans.org/reading-room/whitepapers/analyst/2016-securityanalytics-survey-37467. Accessed 3 Mar 2018

4. Flammini F, Gaglione A, Otello F, Pappalardo A, Pragliola C, Tedesco A (2010) Towards wireless sensor networks for railway infrastructure monitoring. Ansaldo STS Italy, Università di Napoli Federico II

5. Flammini F, Gaglione A, Mazzocca N, Pragliola C (2008) DETECT: a novel framework for the detection of attacks to critical infrastructures. In: Proceedings of ESREL’08, safety, reliability and risk analysis: theory, methods and applications. CRC Press, Taylor & Francis Group, London, pp 105–112

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