Enhancing the Security of OFDM-PONs with Machine Learning Based Device Fingerprint Identification
45th European Conference on Optical Communication (ECOC 2019)(2019)
Abstract
We propose and demonstrate an identity authentication method in OFDM-PON by recognizing device fingerprints of ONUs. Experimental results show that rogue ONU can be detected and 92.43% identification accuracy is achieved. The proposed method can effectively improve the ability of PONs to resist identity spoofing attack.
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