Eavesdropping Detection and Localization in WDM Optical System
Paper in proceeding, 2023
Leveraging our initial work on detecting eavesdropping events in WDM optical systems [1], we propose a mechanism that utilizes bisecting k-means on dynamic optical performance monitoring (OPM) data to initialize the detection. We develop a method to detect and localize single and multiple eavesdropping events in WDM optical systems. Very small losses caused by eavesdropping can be detected using OPM data collected at the receiver, while the in-line OPM data enables localizing single and multiple eavesdropping events.
eavesdropping
machine learning
power
Author
Haokun Song
Rui Lin
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Lena Wosinska
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Paolo Monti
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Yajie Li
Beijing University of Posts and Telecommunications (BUPT)
Jie Zhang
Beijing University of Posts and Telecommunications (BUPT)
Proceedings - 2023 IEEE Future Networks World Forum: Future Networks: Imagining the Network of the Future, FNWF 2023
9798350324587 (ISBN)
6th IEEE Future Networks World Forum, FNWF 2023
Baltimore,MD, USA,
Baltimore,MD, USA,
Providing Resilient & secure networks [Operating on Trusted Equipment] to CriTical infrastructures (PROTECT)
VINNOVA (2020-03506), 2021-02-01 -- 2024-01-31.
Subject Categories
Computer Engineering
Telecommunications
Communication Systems
Computer Systems
Areas of Advance
Information and Communication Technology
DOI
10.1109/FNWF58287.2023.10520648