Cluster-Based Method for Eavesdropping Identification and Localization in Optical Links
Paper in proceeding, 2023
We propose a cluster-based method to detect and locate eavesdropping events in optical line systems characterized by small power losses. Our findings indicate that detecting such subtle losses from eavesdropping can be accomplished solely through optical performance monitoring (OPM) data collected at the receiver. On the other hand, the localization of such events can be effectively achieved by leveraging in-line OPM data.
eavesdropping
power
machine learning
Author
Haokun Song
Beijing University of Posts and Telecommunications (BUPT)
Rui Lin
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Andrea Sgambelluri
Sant'Anna School of Advanced Studies (SSSUP)
Filippo Cugini
Sant'Anna School of Advanced Studies (SSSUP)
Yajie Li
Beijing University of Posts and Telecommunications (BUPT)
Jie Zhang
Beijing University of Posts and Telecommunications (BUPT)
Paolo Monti
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Asia Communications and Photonics Conference, ACP
2162108x (ISSN)
9798350312614 (ISBN)
2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023
Wuhan, China,
Wuhan, China,
Providing Resilient & secure networks [Operating on Trusted Equipment] to CriTical infrastructures (PROTECT)
VINNOVA (2020-03506), 2021-02-01 -- 2024-01-31.
Areas of Advance
Information and Communication Technology
Subject Categories
Communication Systems
Computer Systems
DOI
10.1109/ACP/POEM59049.2023.10369850