Autonomous Security Management in Optical Networks
Paper i proceeding, 2021
The paper describes the Optical Security Manager module and focuses on the role of Machine Learning (ML) techniques. Issues related to the accuracy, run-time complexity and interpretability of ML outputs are described and coping strategies outlined.
Författare
Carlos Natalino Da Silva
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Andrea Di Giglio
Telecom Italia S.P.A
Marco Schiano
Telecom Italia S.P.A
Marija Furdek Prekratic
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings
9489575
978-194358086-6 (ISBN)
Optical Fiber Communications Conference and Exhibition (OFC)
San Francisco, CA, USA,
San Francisco, CA, USA,
Providing Resilient & secure networks [Operating on Trusted Equipment] to CriTical infrastructures (PROTECT)
VINNOVA (2020-03506), 2021-02-01 -- 2024-01-31.
Secured autonomic traffic management for a Tera of SDN flows (TeraFlow)
Europeiska kommissionen (EU) (EC/H2020/101015857), 2021-01-01 -- 2023-06-30.
Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker
Vetenskapsrådet (VR) (2019-05008), 2020-01-01 -- 2023-12-31.
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Telekommunikation
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