Deep Learning-Enhanced Dynamic Photonic Security System Using Multimode VCSELs

Q: What type of study is this?

This is a Experimental Study study.

Nakul Nandhakumar; Zhican Zhou; Hang Lu; Omar Alkhazragi; Tien Khee Ng; Boon S. Ooi; Yating Wan

doi:10.1364/cleo_si.2025.ss126_3

January 1, 2025

Deep Learning-Enhanced Dynamic Photonic Security System Using Multimode VCSELs

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Key Points

The system achieves ultra-fast key distribution in less than 10 ns, enhancing security performance.
It utilizes dynamic physical unclonable functions generated by multimode VCSELs, offering high specificity.
Deep learning techniques are integrated for improved authentication processes and security system efficiency.
The solution is particularly effective in anti-counterfeiting applications, reflecting a significant advancement in security technology.

Implication

Photonic security system improves authentication and key distribution speed using multimode VCSELs, indicating strong anti-counterfeiting potential.

Abstract

We present a photonic security system leveraging dynamic physical unclonable functions generated by multimode VCSELs, combined with deep learning-enhanced authentication. This system enables ultra-fast key distribution (<10 ns) and ~100% specificity, ideal for robust anti-counterfeiting.

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Cite This Study

Nandhakumar et al. (2025) studied this question.

synapsesocial.com/papers/68d463f131b076d99fa6377d https://doi.org/10.1364/cleo_si.2025.ss126_3

View Full Paper

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Deep Learning-Enhanced Dynamic Photonic Security System Using Multimode VCSELs

Key Points

Implication

Abstract

Discussion

Cite This Study

Deep Learning-Enhanced Dynamic Photonic Security System Using Multimode VCSELs

Key Points

Implication

Abstract

Discussion

Cite This Study

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