• Publications
  • Influence
Physical Unclonable Functions and Applications: A Tutorial
TLDR
This paper describes the use of physical unclonable functions (PUFs) in low-cost authentication and key generation applications. Expand
  • 525
  • 58
  • PDF
Secure and robust error correction for physical unclonable functions
TLDR
We propose a new syndrome coding scheme that limits the amount of leaked information by the PUF error-correcting codes. Expand
  • 299
  • 20
  • PDF
A Lockdown Technique to Prevent Machine Learning on PUFs for Lightweight Authentication
TLDR
We present a lightweight PUF-based authentication approach that is practical in settings where a server authenticates a device, and for use cases where the number of authentications is limited over a device's lifetime. Expand
  • 92
  • 17
  • PDF
Efficient Fuzzy Extraction of PUF-Induced Secrets: Theory and Applications
TLDR
We derive new considerably tighter bounds for PUF-induced distributions that suffer from, e.g., bias or spatial correlations. Expand
  • 56
  • 7
  • PDF
Recombination of Physical Unclonable Functions
TLDR
A new Physical Unclonable Function (PUF) construction is described, by treating silicon unique features extracted from PUFs circuits as “genetic material” unique to each silicon, and recombining this chip-unique material in a way to obtain a combination of advantages not possible with the original PUF circuits, including altering PUF output statistics to better suit PUF-based key generation. Expand
  • 42
  • 6
  • PDF
A noise bifurcation architecture for linear additive physical functions
TLDR
We present the first architecture for linear additive physical functions where the noise seen by the adversary and the noise Seen by the verifier are bifurcated by using a randomized decimation technique and a novel response recovery method at an authentication verification server. Expand
  • 53
  • 5
  • PDF
Trapdoor Computational Fuzzy Extractors and Stateless Cryptographically-Secure Physical Unclonable Functions
We present a fuzzy extractor whose security can be reduced to the hardness of Learning Parity with Noise (LPN) and can efficiently correct a constant fraction of errors in a biometric source with aExpand
  • 55
  • 4
  • PDF
Cherry-Picking Reliable PUF Bits With Differential Sequence Coding
  • M. Hiller, M. Yu, G. Sigl
  • Computer Science
  • IEEE Transactions on Information Forensics and…
  • 1 September 2016
TLDR
We present differential sequence coding that scales efficiently across larger block sizes without having the super-linear increase in decoding complexity of prior approaches without increasing the implementation size of the key generation module noticeably. Expand
  • 34
  • 4
Trapdoor Computational Fuzzy Extractors
TLDR
We describe a method of cryptographically-secure key extraction from a noisy biometric source that uses additional confidence information produced by the source for polynomial-time key recovery even under high-noise settings. Expand
  • 10
  • 4
  • PDF
Lightweight and Secure PUF Key Storage Using Limits of Machine Learning
TLDR
A lightweight and secure key storage scheme using silicon Physical Unclonable Functions (PUFs) is described. Expand
  • 93
  • 3
  • PDF