Unclonable photonic keys hardened against machine learning attacks-Reference-Cited by-同舟云学术

Unclonable photonic keys hardened against machine learning attacks

Published:2020-01-01 Issue:1 Volume:5 Page:010803
ISSN:2378-0967
Container-title:APL Photonics
language:en
Short-container-title:APL Photonics

Author:

Bosworth Bryan T.¹,Atakhodjaev Iskandar A.¹,Kossey Michael R.¹,Grubel Brian C.¹,Vresilovic Daniel S.¹,Stroud Jasper R.¹,MacFarlane Neil¹,Villalba Jesús¹,Dehak Najim¹,Cooper A. Brinton¹^ORCID,Foster Mark A.¹,Foster Amy C.¹

Affiliation:

1. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA

Funder

National Science Foundation

Intelligence Advanced Research Projects Activity

Office of the Provost, Johns Hopkins University

Publisher

AIP Publishing

Subject

Computer Networks and Communications,Atomic and Molecular Physics, and Optics

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5100178

Reference43 articles.

1. Investigation of Deep Learning Attacks on Nonlinear Silicon Photonic PUFs

2. Machine learning and structural characteristics for reverse engineering

3. Efficient Padding Oracle Attacks on Cryptographic Hardware

4. On the Pitfalls of Using Arbiter-PUFs as Building Blocks

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