Cluster-based Method for Eavesdropping Identification and Localization in Optical Links

Song, Haokun, Lin, Rui, Sgambelluri, Andrea, Cugini, Filippo, Li, Yajie, Zhang, Jie, Monti, Paolo

arXiv.org Machine Learning 

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.

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