Channel Characteristics Based Adjustable Fingerprint for Identity Authentication in WDM-PON With Deep Neural Networks

Kun Wu,Hongxiang Wang,Yuefeng Ji

doi:10.1109/jphot.2022.3158622

Abstract

Wavelength-division-multiplexed passive optical network (WDM-PON) has been widely deployed for the high-speed, reliable transmission and low-cost properties. The physical layer identity authentication in WDM-PON becomes increasingly prominent. Recently, many device fingerprint based identity authentication schemes are proposed. However, these schemes only realize constant fingerprint, which will be acquired by illegal ONU after optical spectrum analysis. Therefore, the higher-level security requirement cannot be satisfied. To solve the problem, we propose a physical layer identity authentication method in WDM-PON by exploiting the channel characteristics based adjustable fingerprint with deep neural networks (DNNs). By secretly negotiating with legal optical network units (ONUs) on the lengths of the local fibers applied by them, the optical line terminal (OLT) can acquire the unique channel characteristics fingerprint obtained by each legal ONU. It should be noted that the fingerprint can be adjusted by modifying the length of the local fiber. Moreover, the same number of DNNs as legal ONUs are trained for fingerprint identification. Simulation results show 100% identification accuracy for illegal ONU when the length deviation between two fibers applied by legal ONU and illegal ONU is greater than 1.5 km. Meanwhile, the identity of each legal ONU can be recognized with 100% accuracy.

Highlights

Wavelength-division-multiplexed passive optical network (WDM-PON) has been widely deployed for the highspeed, reliable transmission and low-cost properties
The lengths of the local fibers applied by each legal optical network units (ONUs) are set to 35 km, while the length of the local fiber used by the optical line terminal (OLT) is 0 km
The accuracy to identify the illegal ONU is 100% when the length deviation between the two local fibers applied by legal ONU and illegal ONU is greater than 1.5 km, while the identification accuracy for illegal ONU is not 100% in other cases

Summary

INTRODUCTION

Public-key encryption algorithms, a reliable certificate agency (CA) is required to distribute the digital certification for. In order to provide more secure identity authentication in WDM-PON, the physical layer secure schemes have been studied. By using the non-ideal devices of the legal ONUs as the device fingerprint of each legal ONU, the physical layer identity authentication schemes with constant fingerprint are realized. Facing the changeable and unpredictable attack scenarios, these identity authentication schemes with constant fingerprint cannot meet the higher-level security requirement. A physical layer identity authentication method by applying the channel characteristics based adjustable fingerprint with DNNs in WDM-PON is proposed. At the OLT end, the identity of each ONU is authenticated by recognizing these fingerprints with DNNs. Compared to the above secure schemes, our proposed method realizes adjustable fingerprint, which can be changed by modifying the length of the local fiber applied by each legal ONU. The proposed method is fully compatible with current PON infrastructure, guaranteeing the lower cost compared with those methods with specially designed hardware structure [22]

DNN Training

Identity Authentication

Data Transmission

CONCLUSION