A Low-Cost Unified Experimental FPGA Board for Cryptography Applications

This paper describes the evaluation of available experimental boards, the comparison of their supported set of experiments and other aspects. The second part of this evaluation is focused on the design process of the PCB (Printed Circuit Board) for an FPGA (Field Programmable Gate Array) based cryptography environment suitable for evaluating the latest trends in the IC (Integrated Circuit) security like Side–Channel Attacks (SCA) or Physically Unclonable Function (PUF). It leads to many criteria affecting the design process and also the suitability for evaluating and measuring results of the attacks and their countermeasures. The developed system should be open, versatile and unrestricted by the U.S. law [1]

Watermarking FPGA Bitfile for Intellectual Property Protection

Intellectual property protection (IPP) of hardware designs is the most important requirement for many Field Programmable Gate Array (FPGA) intellectual property (IP) vendors. Digital watermarking has become an innovative technology for IPP in recent years. Existing watermarking techniques have successfully embedded watermark into IP cores. However, many of these techniques share two specific weaknesses: 1) They have extra overhead, and are likely to degrade performance of design; 2) vulnerability to removing attacks. We propose a novel watermarking technique to watermark FPGA bitfile for addressing these weaknesses. Experimental results and analysis show that the proposed technique incurs zero overhead and it is robust against removing attacks

A Random Number Generator Using Ring Oscillators and SHA-256 as Post-Processing

Today, cryptographic security depends primarily on having strong keys and keeping them secret. The keys should be produced by a reliable and robust to external manipulations generators of random numbers. To hamper different attacks, the generators should be implemented in the same chip as a cryptographic system using random numbers. It forces a designer to create a random number generator purely digitally. Unfortunately, the obtained sequences are biased and do not pass many statistical tests. Therefore an output of the random number generator has to be subjected to a transformation called post-processing. In this paper the hash function SHA-256 as post-processing of bits produced by a combined random bit generator using jitter observed in ring oscillators (ROs) is proposed. All components – the random number generator and the SHA-256, are implemented in a single Field Programmable Gate Array (FPGA). We expect that the proposed solution, implemented in the same FPGA together with a cryptographic system, is more attack-resistant owing to many sources of randomness with significantly different nominal frequencies

Producing Random Bits with Delay-Line Based Ring Oscillators

One of the sources of randomness for a random bit generator (RBG) is jitter present in rectangular signals produced by ring oscillators (ROs). This paper presents a novel approach for the design of delays used in these oscillators. We suggest using delay elements made on carry4 primitives instead of series of inverters or latches considered in the literature. It enables the construction of many high frequency ring oscillators with different nominal frequencies in the same field programmable gate array (FPGA). To assess the unpredictability of bits produced by RO-based RBG, the restarts mechanism, proposed in earlier papers, was used. The output sequences pass all NIST 800-22 statistical tests for smaller number of ring oscillators than the constructions described in the literature. Due to the number of ROs with different nominal frequencies and the method of construction of carry4 primitives, it is expected that the proposed RBG is more robust to cryptographic attacks than RBGs using inverters or latches as delay element

On the Entropy of Oscillator-Based True Random Number Generators under Ionizing Radiation

The effects of ionizing radiation on field-programmable gate arrays (FPGAs) have been investigated in depth during the last decades. The impact of these effects is typically evaluated on implementations which have a deterministic behavior. In this article, two well-known true-random number generators (TRNGs) based on sampling jittery signals have been exposed to a Co-60 radiation source as in the standard tests for space conditions. The effects of the accumulated dose on these TRNGs, an in particular, its repercussion over their randomness quality (e.g., entropy or linear complexity), have been evaluated by using two National Institute of Standards and Technology (NIST) statistical test suites. The obtained results clearly show how the degradation of the statistical properties of these TRNGs increases with the accumulated dose. It is also notable that the deterioration of the TRNG (non-deterministic component) appears before that the degradation of the deterministic elements in the FPGA, which compromises the integrated circuit lifetime.Ministerio de Economía y Competitividad (ESP-2015-68245-C4-1-P)Ministerio de Economía y Competitividad (ESP-2015-68245-C4-4-P)Ministerio de Economía y Empresa (TIN2016-79095-C2-2-R)CAM (S2013/ICE-3095

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

© 2016 Cheung, Schultz and Luk.NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation

Power Side Channels in Security ICs: Hardware Countermeasures

Power side-channel attacks are a very effective cryptanalysis technique that can infer secret keys of security ICs by monitoring the power consumption. Since the emergence of practical attacks in the late 90s, they have been a major threat to many cryptographic-equipped devices including smart cards, encrypted FPGA designs, and mobile phones. Designers and manufacturers of cryptographic devices have in response developed various countermeasures for protection. Attacking methods have also evolved to counteract resistant implementations. This paper reviews foundational power analysis attack techniques and examines a variety of hardware design mitigations. The aim is to highlight exposed vulnerabilities in hardware-based countermeasures for future more secure implementations