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Optical Fiber Communication Conference

Detection of abnormal activities on a SM or MM fiber

Stefan Karlsson, Mikael Andersson, Rui Lin, Lena Wosinska, Paolo Monti

Published Jan 1, 2023• 7 citations
Publisher

Abstract

We demonstrate eavesdrop detection based on polarization signatures by analyzing polarization state changes at the receiver. We identify changes related to the normal operation and the ones caused by eavesdropping.
DOI
10.1364/ofc.2023.m3z.6

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The main topic of this paper is the detection state of polarization changes to enhance data security in fiber cable paths. The changes are generated by fiber manipulation or movements, which suggest potential security threats. Our designed system detects these changes using a polarization beam splitter and a pair of photodetectors. The values are subtracted from each other, sampled, and sent for analysis. The software detector applies FFT onto the signal and normalizes the output. The last step compares the sum of the bottom eighth of the spectrum against the threshold.
Fiber eavesdropping severely endangers the confidentiality of data transmitted in optical networks. Therefore, it is necessary to explore how to detect and locate fiber eavesdropping in an effective approach. To leverage the advantages of the state of polarization (SOP) in detecting various abnormal events while addressing its challenges in acquiring the SOP of different fiber links, we propose a multi-channel joint SOP estimation scheme to estimate the SOP of different fiber spans. Based on the proposed scheme, we provide a comprehensive solution for fiber eavesdropping location and detection in optical communication systems. In this solution, the estimated SOP and optical performance monitoring (OPM) data are utilized for rapid fiber eavesdropping detection and coarse location at the span level. The effectiveness of the solution is validated by experiments. In the aspect of detection, we achieve the detection of the start or end of fiber eavesdropping, the overlapping of fiber eavesdropping and abnormal events, and other abnormal events. The overall accuracy is 99.77%. In the aspect of location, we can locate the fiber span that has been eavesdropped.