Optical Fingerprint: a Possible Direction to Physical Layer Security, Authentication, Identification, and Monitoring

Potì, L.; Goki, Pantea Nadimi; Mulugeta, Thomas Teferi; Sambo, N.; Caldelli, Roberto

doi:10.23919/fitce56290.2022.9934467

Cited by 3 publications

(7 citation statements)

References 10 publications

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Section: Discussionmentioning

confidence: 99%

Device Fingerprint as a Transmission Security Paradigm

Nadimi Goki,

Teferi Mulugeta,

Sambo

et al. 2023

Optoelectronics - Recent Advances

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Optoelectronics plays a crucial role in the field of telecommunications and networks. Specifically, optoelectronic constructions serve as sources, detectors, and light controllers in communication and optical network systems. One of the requirements of a secure system is evaluating the optical components of optoelectronic assemblies and ensuring their security against malicious attacks. To address this, we introduce the concept of optical fingerprints in optical communications and networks. This concept includes reading the fingerprints of devices, sub-systems, and systems to address services that comprise security, authentication, identification, and monitoring. Using optical fingerprints as a signature of optical fibers, it becomes possible to identify and evaluate any optical component of optoelectronic assemblies through their pigtail.

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Section: Discussionmentioning

confidence: 99%

Device Fingerprint as a Transmission Security Paradigm

Nadimi Goki,

Teferi Mulugeta,

Sambo

et al. 2023

Optoelectronics - Recent Advances

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“…Physically invading the system will cause a change in the system signature that could confirm the presence of an imposter. Even digital invaders with advanced machine learning (ML) knowledge cannot predict the system's signature [30] because every system or device has its own unique and unpredictable signature [31,32]. In the following sections, we demonstrate the procedure of reading signatures and provide an example of a protocol that benefits from this identification.…”

Section: Reading the Network's Constituent Devices' Signaturesmentioning

confidence: 99%

“…In [31][32][33][34][35][36][37], we evaluated the obtained signatures' uniqueness and reproducibility using Hamming distance. In this work, we further assess the signatures to complete the evaluation of the model's performance.…”

Section: Signature Evaluationmentioning

confidence: 99%

“…One of the most significant ways to explore a signature's cybersecurity is by considering the random structure of the produced signatures (bits). In [32], we demonstrated the strength of the signature against a brute force attack using Hamming distance. Here, STS with h = 0 verifies the results in [32].…”

Section: (D) Statistical Test Suite (Sts)mentioning

confidence: 99%

“…In [32], we demonstrated the strength of the signature against a brute force attack using Hamming distance. Here, STS with h = 0 verifies the results in [32].…”

Section: (D) Statistical Test Suite (Sts)mentioning

confidence: 99%

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Optical Systems Identification through Rayleigh Backscattering

Goki

Mulugeta

Caldelli

et al. 2023

Sensors

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We introduce a technique to generate and read the digital signature of the networks, channels, and optical devices that possess the fiber-optic pigtails to enhance physical layer security (PLS). Attributing a signature to the networks or devices eases the identification and authentication of networks and systems thus reducing their vulnerability to physical and digital attacks. The signatures are generated using an optical physical unclonable function (OPUF). Considering that OPUFs are established as the most potent anti-counterfeiting tool, the created signatures are robust against malicious attacks such as tampering and cyber attacks. We investigate Rayleigh backscattering signal (RBS) as a strong OPUF to generate reliable signatures. Contrary to other OPUFs that must be fabricated, the RBS-based OPUF is an inherent feature of fibers and can be easily obtained using optical frequency domain reflectometry (OFDR). We evaluate the security of the generated signatures in terms of their robustness against prediction and cloning. We demonstrate the robustness of signatures against digital and physical attacks confirming the unpredictability and unclonability features of the generated signatures. We explore signature cyber security by considering the random structure of the produced signatures. To demonstrate signature reproducibility through repeated measurements, we simulate the signature of a system by adding a random Gaussian white noise to the signal. This model is proposed to address services including security, authentication, identification, and monitoring.

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