Cluster-Based Method for Eavesdropping Identification and Localization in Optical Links
Paper i 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

Författare

Haokun Song

Beijing University of Posts and Telecommunications (BUPT)

Rui Lin

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Andrea Sgambelluri

Scuola Superiore Sant'Anna (SSSUP)

Filippo Cugini

Scuola Superiore Sant'Anna (SSSUP)

Yajie Li

Beijing University of Posts and Telecommunications (BUPT)

Jie Zhang

Beijing University of Posts and Telecommunications (BUPT)

Paolo Monti

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

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,

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

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

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Kommunikationssystem

Datorsystem

DOI

10.1109/ACP/POEM59049.2023.10369850

Mer information

Senast uppdaterat

2024-02-05