Machine Learning Analysis of Polarization Signatures for Distinguishing Harmful from Non-harmful Fiber Events
Paper in proceeding, 2024

Secure and reliable data transmission in optical networks is essential for supporting high-speed internet services. Optical fibers, the enabler of global connectivity for millions of users, are vulnerable to various potentially harmful events including mechanical failures, like fiber cuts, and malicious physical layer attacks, such as eavesdropping. These incidents can degrade network performance, breach privacy and integrity through unauthorized access to the transmitted data, and cause significant financial and data loss. It is, therefore, crucial to detect and classify the malicious events. Continuous monitoring of polarization state changes, combined with application of machine learning algorithms, enables detection of deviations in the polarization patterns caused by the harmful events. In this study, we introduce a method that detects and identifies potential harmful events in optical networks. By using a Histogram Gradient Boosting classifier within our machine learning framework, we achieve 97.94% detection accuracy of the harmful and non-harmful events.

polarization signatures

harmful vibration

eavesdropping

machine learning

Polarization state movement

Author

Leyla Sadighi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Stefan Karlsson

Swedish Defence Materiel Administration

Lena Wosinska

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Marija Furdek Prekratic

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

International Conference on Transparent Optical Networks

21627339 (ISSN)


9798350377309 (ISBN)

24th International Conference on Transparent Optical Networks, ICTON 2024
Bari, Italy,

Providing Resilient & secure networks [Operating on Trusted Equipment] to CriTical infrastructures (PROTECT)

VINNOVA (2020-03506), 2021-02-01 -- 2024-01-31.

InfraTrust: Enabling trustworthy services over vulnerable physical network infrastructure

Swedish Research Council (VR), 2024-01-01 -- 2027-12-31.

5G Trusted And seCure network servICes (5G-TACTIC)

European Commission (EC) (EC/H2020/101127973), 2023-12-01 -- 2026-11-30.

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Computer Systems

DOI

10.1109/ICTON62926.2024.10648140

More information

Latest update

9/25/2024