Eavesdropping Detection and Localization in WDM Optical System
Paper i 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

Författare

Haokun Song

Rui Lin

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Lena Wosinska

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Paolo Monti

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

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,

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

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

Ämneskategorier

Datorteknik

Telekommunikation

Kommunikationssystem

Datorsystem

Styrkeområden

Informations- och kommunikationsteknik

DOI

10.1109/FNWF58287.2023.10520648

Mer information

Senast uppdaterat

2024-06-10