1 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Designing a Photonic Physically Unclonable Function Having Resilience to Machine Learning Attacks
Elena R. Henderson, Jessie M. Henderson, Hiva Shahoei +4
Physically unclonable functions (PUFs) are designed to act as device 'fingerprints.' Given an input challenge, the PUF circuit should produce an unpredictable response for use in s…
A Photonic Physically Unclonable Function's Resilience to Multiple-Valued Machine Learning Attacks
Jessie M. Henderson, Elena R. Henderson, Clayton A. Harper +5
Physically unclonable functions (PUFs) identify integrated circuits using nonlinearly-related challenge-response pairs (CRPs). Ideally, the relationship between challenges and corr…
CNN-Assisted Steganography -- Integrating Machine Learning with Established Steganographic Techniques
Andrew Havard, Theodore Manikas, Eric C. Larson +1
We propose a method to improve steganography by increasing the resilience of stego-media to discovery through steganalysis. Our approach enhances a class of steganographic approach…