Optical identification using physical unclonable functions

被引:6
作者
Goki, Pantea Nadimi [1 ,2 ]
Civelli, Stella [2 ,3 ]
Parente, Emanuele [2 ]
Caldelli, Roberto [4 ,5 ]
Mulugeta, Thomas Teferi [2 ]
Sambo, Nicola [2 ]
Secondini, Marco
Poti, Luca [1 ,5 ]
机构
[1] CNIT, Photon Networks & Technol Lab, Via G Moruzzi 1, I-56124 Pisa, Italy
[2] Scuola Super Sant Anna, TeCIP Inst, Via G Moruzzi 1, I-56124 Pisa, Italy
[3] CNR IEIIT, Via Caruso 16, I-56122 Pisa, Italy
[4] CNIT Florence Res Unit, Viale Morgagni 65, I-50134 Florence, Italy
[5] Univ Mercatorum, Piazza Mattei 10, I-00186 Rome, Italy
关键词
Security; Optical fiber networks; Adaptive optics; Protocols; Optical devices; Cryptography; Optical transmitters; FREQUENCY-DOMAIN REFLECTOMETRY; AUTHENTICATION; LASER;
D O I
10.1364/JOCN.489889
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this work, the concept of optical identification (OI) based on physical unclonable functions is introduced for the first time, to our knowledge, in optical communication systems and networks. The OI assigns an optical fingerprint and the corresponding digital representation to each sub-system of the network and estimates its reliability in different measures. We highlight the large potential applications of OI as a physical layer approach for security, identification, authentication, and monitoring purposes. To identify most of the sub-systems of a network, we propose to use the Rayleigh backscattering pattern, which is an optical physical unclonable function and allows OI to be achieved with a simple procedure and without additional devices. The applications of OI to fiber and path identification in a network and to the authentication of users in a quantum key distribution system are described.
引用
收藏
页码:E63 / E73
页数:11
相关论文
共 52 条
[1]  
Antonik P, 2018, IEEE IJCNN
[2]  
Bennett C H., 1984, Theor. Comput. Sci, V560, P175, DOI [10.1016/j.tcs.2014.05.025, DOI 10.1016/J.TCS.2014.05.025, 10.1016/j.tcs.2011.08.039, DOI 10.1016/J.TCS.2011.08.039]
[3]  
Bloch M., 2011, Physical-Layer Security: From Information Theory to Security Engineering
[4]  
Cavaliere F., 2020, Quantum Reports, V2, P80, DOI DOI 10.3390/QUANTUM2010007
[5]   Determining image origin and integrity using sensor noise [J].
Chen, Mo ;
Fridrich, Jessica ;
GoIjan, Miroslav ;
Lukas, Jan .
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2008, 3 (01) :74-90
[6]  
Chen W., 2022, J. Phys. Conf. Ser., V2237
[7]   Incoherent Optical Frequency-Domain Reflectometry Based on Homodyne Electro-Optic Downconversion for Fiber-Optic Sensor Interrogation [J].
Clement, Juan ;
Maestre, Haroldo ;
Torregrosa, German ;
Fernandez-Pousa, Carlos R. .
SENSORS, 2019, 19 (09)
[8]   Compensation of laser frequency tuning nonlinearity of a long range OFDR using deskew filter [J].
Ding, Zhenyang ;
Yao, X. Steve ;
Liu, Tiegen ;
Du, Yang ;
Liu, Kun ;
Jiang, Junfeng ;
Meng, Zhuo ;
Chen, Hongxin .
OPTICS EXPRESS, 2013, 21 (03) :3826-3834
[9]   Unclonable Optical Fiber Identification Based on Rayleigh Backscattering Signatures [J].
Du, Yang ;
Jothibasu, Sasi ;
Zhuang, Yiyang ;
Zhu, Chen ;
Huang, Jie .
JOURNAL OF LIGHTWAVE TECHNOLOGY, 2017, 35 (21) :4634-4640
[10]   Identify the Device Fingerprint of OFDM-PONsWith a Noise-Model-Assisted CNN for Enhancing Security [J].
Fan, Chengpeng ;
Gong, Huiyuan ;
Cheng, Mengfan ;
Ye, Bolin ;
Deng, Lei ;
Yang, Qi ;
Liu, Deming .
IEEE PHOTONICS JOURNAL, 2021, 13 (04)