Sökning: id:"swepub:oai:research.chalmers.se:a0b8f3d9-3aa3-476a-ade6-d082b73b511c" >
Machine Learning fo...
Machine Learning for Optical Network Security Monitoring: A Practical Perspective
-
- Furdek Prekratic, Marija, 1985 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
-
- Natalino Da Silva, Carlos, 1987 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
-
Lipp, Fabian (författare)
-
visa fler...
-
Hock, David (författare)
-
- Di Giglio, Andrea (författare)
- Telecom Italia S.P.A
-
- Schiano, Marco (författare)
- Telecom Italia S.P.A
-
visa färre...
-
Chalmers tekniska högskola Telecom Italia SP.A (creator_code:org_t)
- 2020
- 2020
- Engelska.
-
Ingår i: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 38:11, s. 2860-2871
- Relaterad länk:
-
https://research.cha... (primary) (free)
-
visa fler...
-
https://doi.org/10.1...
-
https://research.cha...
-
https://research.cha...
-
visa färre...
Abstract
Ämnesord
Stäng
- In order to accomplish cost-efficient management of complex optical communication networks, operators are seeking automation of network diagnosis and management by means of Machine Learning (ML). To support these objectives, new functions are needed to enable cognitive, autonomous management of optical network security. This paper focuses on the challenges related to the performance of ML-based approaches for detection and localization of optical-layer attacks, and to their integration with standard Network Management Systems (NMSs). We propose a framework for cognitive security diagnostics that comprises an attack detection module with Supervised Learning (SL), Semi-Supervised Learning (SSL) and Unsupervised Learning (UL) approaches, and an attack localization module that deduces the location of a harmful connection and/or a breached link. The influence of false positives and false negatives is addressed by a newly proposed Window-based Attack Detection (WAD) approach. We provide practical implementation guidelines for the integration of the framework into the NMS and evaluate its performance in an experimental network testbed subjected to attacks, resulting with the largest optical-layer security experimental dataset reported to date.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Telekommunikation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Telecommunications (hsv//eng)
Nyckelord
- monitoring
- optical network security
- attack detection
- machine learning
Publikations- och innehållstyp
- for (ämneskategori)
- ref (ämneskategori)
Hitta via bibliotek
Till lärosätets databas