Multiple observations for secret-key binding with SRAM PUFs

We present a new Multiple-Observations (MO) helper data scheme for secret-key binding to an SRAM-PUF. This MO scheme binds a single key to multiple enrollment observations of the SRAM-PUF. Performance is improved in comparison to classic schemes which generate helper data based on a single enrollment observation. The performance increase can be explained by the fact that the reliabilities of the different SRAM cells are modeled (implicitly) in the helper data. We prove that the scheme achieves secret-key capacity for any number of enrollment observations, and, therefore, it is optimal. We evaluate performance of the scheme using Monte Carlo simulations, where an off-the-shelf LDPC code is used to implement the linear error-correcting code. Another scheme that models the reliabilities of the SRAM cells is the so-called Soft-Decision (SD) helper data scheme. The SD scheme considers the one-probabilities of the SRAM cells as an input, which in practice are not observable. We present a new strategy for the SD scheme that considers the binary SRAM-PUF observations as an input instead and show that the new strategy is optimal and achieves the same reconstruction performance as the MO scheme. Finally, we present a variation on the MO helper data scheme that updates the helper data sequentially after each successful reconstruction of the key. As a result, the error-correcting performance of the scheme is improved over time

Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping

In this paper, we provide for the first time a systematic comparison of distribution matching (DM) and sphere shaping (SpSh) algorithms for short blocklength probabilistic amplitude shaping. For asymptotically large blocklengths, constant composition distribution matching (CCDM) is known to generate the target capacity-achieving distribution. As the blocklength decreases, however, the resulting rate loss diminishes the efficiency of CCDM. We claim that for such short blocklengths and over the additive white Gaussian channel (AWGN), the objective of shaping should be reformulated as obtaining the most energy-efficient signal space for a given rate (rather than matching distributions). In light of this interpretation, multiset-partition DM (MPDM), enumerative sphere shaping (ESS) and shell mapping (SM), are reviewed as energy-efficient shaping techniques. Numerical results show that MPDM and SpSh have smaller rate losses than CCDM. SpSh--whose sole objective is to maximize the energy efficiency--is shown to have the minimum rate loss amongst all. We provide simulation results of the end-to-end decoding performance showing that up to 1 dB improvement in power efficiency over uniform signaling can be obtained with MPDM and SpSh at blocklengths around 200. Finally, we present a discussion on the complexity of these algorithms from the perspective of latency, storage and computations.Comment: 18 pages, 10 figure

Partial Enumerative Sphere Shaping

The dependency between the Gaussianity of the input distribution for the additive white Gaussian noise (AWGN) channel and the gap-to-capacity is discussed. We show that a set of particular approximations to the Maxwell-Boltzmann (MB) distribution virtually closes most of the shaping gap. We relate these symbol-level distributions to bit-level distributions, and demonstrate that they correspond to keeping some of the amplitude bit-levels uniform and independent of the others. Then we propose partial enumerative sphere shaping (P-ESS) to realize such distributions in the probabilistic amplitude shaping (PAS) framework. Simulations over the AWGN channel exhibit that shaping 2 amplitude bits of 16-ASK have almost the same performance as shaping 3 bits, which is 1.3 dB more power-efficient than uniform signaling at a rate of 3 bit/symbol. In this way, required storage and computational complexity of shaping are reduced by factors of 6 and 3, respectively.Comment: 6 pages, 6 figure

Efficient key generation scheme for SRAM-PUFs using polar codes

Physical unclonable functions (PUFs) are a new promising means to realize cryptographic scenarios such as identification, authentication and secret key generation. PUFs avoid the need for key storage, because the device-unique randomness can be translated into a cryptographic key. SRAM-PUFs enjoy the properties that, while being easily evaluated (after a device power-up), they are unique, reproducible, physically unclonable and unpredictable. Error correction codes (ECCs) are essential blocks of secret-generation schemes, since PUF observations are always effected by noise and environmental changes. In this paper, we propose practical error correction schemes for PUF-based secret generation that are based on polar codes. The proposed scheme could generate a 128-bit key or 256-bit key using less PUF bits and helper data bits than before and achieve a low failure probability for a practical SRAM-PUFs application with error probability between 15% and 25%. Therefore SRAM-PUFs are considered to combine very well with authentication and unique cryptographic key generation for resource constrained devices

Information Theoretical Analysis of Identification based on Active Content Fingerprinting

Content fingerprinting and digital watermarking are techniques that are used for content protection and distribution monitoring. Over the past few years, both techniques have been well studied and their shortcomings understood. Recently, a new content fingerprinting scheme called {\em active content fingerprinting} was introduced to overcome these shortcomings. Active content fingerprinting aims to modify a content to extract robuster fingerprints than the conventional content fingerprinting. Moreover, contrary to digital watermarking, active content fingerprinting does not embed any message independent of contents thus does not face host interference. The main goal of this paper is to analyze fundamental limits of active content fingerprinting in an information theoretical framework.Comment: 35th WIC Symposium on Information Theory in the Benelu