1,541 research outputs found

    Efficient computation of hashes

    Get PDF
    The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced

    Efficient hardware implementations of high throughput SHA-3 candidates keccak, luffa and blue midnight wish for single- and multi-message hashing

    Get PDF
    In November 2007 NIST announced that it would organize the SHA-3 competition to select a new cryptographic hash function family by 2012. In the selection process, hardware performances of the candidates will play an important role. Our analysis of previously proposed hardware implementations shows that three SHA-3 candidate algorithms can provide superior performance in hardware: Keccak, Luffa and Blue Midnight Wish (BMW). In this paper, we provide efficient and fast hardware implementations of these three algorithms. Considering both single- and multi-message hashing applications with an emphasis on both speed and efficiency, our work presents more comprehensive analysis of their hardware performances by providing different performance figures for different target devices. To our best knowledge, this is the first work that provides a comparative analysis of SHA-3 candidates in multi-message applications. We discover that BMW algorithm can provide much higher throughput than previously reported if used in multi-message hashing. We also show that better utilization of resources can increase speed via different configurations. We implement our designs using Verilog HDL, and map to both ASIC and FPGA devices (Spartan3, Virtex2, and Virtex 4) to give a better comparison with those in the literature. We report total area, maximum frequency, maximum throughput and throughput/area of the designs for all target devices. Given that the selection process for SHA3 is still open; our results will be instrumental to evaluate the hardware performance of the candidates

    An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

    Full text link
    Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

    A Standalone FPGA-based Miner for Lyra2REv2 Cryptocurrencies

    Full text link
    Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms, and it is used as a proof-of-work function in several cryptocurrencies. The most crucial and exotic hashing algorithm in the Lyra2REv2 chain is a specific instance of the general Lyra2 algorithm. This work presents the first hardware implementation of the specific instance of Lyra2 that is used in Lyra2REv2. Several properties of the aforementioned algorithm are exploited in order to optimize the design. In addition, an FPGA-based hardware implementation of a standalone miner for Lyra2REv2 on a Xilinx Multi-Processor System on Chip is presented. The proposed Lyra2REv2 miner is shown to be significantly more energy efficient than both a GPU and a commercially available FPGA-based miner. Finally, we also explain how the simplified Lyra2 and Lyra2REv2 architectures can be modified with minimal effort to also support the recent Lyra2REv3 chained hashing algorithm.Comment: 13 pages, accepted for publication in IEEE Trans. Circuits Syst. I. arXiv admin note: substantial text overlap with arXiv:1807.0576

    Quantum Algorithms for Boolean Equation Solving and Quantum Algebraic Attack on Cryptosystems

    Get PDF
    Decision of whether a Boolean equation system has a solution is an NPC problem and finding a solution is NP hard. In this paper, we present a quantum algorithm to decide whether a Boolean equation system FS has a solution and compute one if FS does have solutions with any given success probability. The runtime complexity of the algorithm is polynomial in the size of FS and the condition number of FS. As a consequence, we give a polynomial-time quantum algorithm for solving Boolean equation systems if their condition numbers are small, say polynomial in the size of FS. We apply our quantum algorithm for solving Boolean equations to the cryptanalysis of several important cryptosystems: the stream cipher Trivum, the block cipher AES, the hash function SHA-3/Keccak, and the multivariate public key cryptosystems, and show that they are secure under quantum algebraic attack only if the condition numbers of the corresponding equation systems are large. This leads to a new criterion for designing cryptosystems that can against the attack of quantum computers: their corresponding equation systems must have large condition numbers

    Estimating the cost of generic quantum pre-image attacks on SHA-2 and SHA-3

    Get PDF
    We investigate the cost of Grover's quantum search algorithm when used in the context of pre-image attacks on the SHA-2 and SHA-3 families of hash functions. Our cost model assumes that the attack is run on a surface code based fault-tolerant quantum computer. Our estimates rely on a time-area metric that costs the number of logical qubits times the depth of the circuit in units of surface code cycles. As a surface code cycle involves a significant classical processing stage, our cost estimates allow for crude, but direct, comparisons of classical and quantum algorithms. We exhibit a circuit for a pre-image attack on SHA-256 that is approximately 2153.82^{153.8} surface code cycles deep and requires approximately 212.62^{12.6} logical qubits. This yields an overall cost of 2166.42^{166.4} logical-qubit-cycles. Likewise we exhibit a SHA3-256 circuit that is approximately 2146.52^{146.5} surface code cycles deep and requires approximately 2202^{20} logical qubits for a total cost of, again, 2166.52^{166.5} logical-qubit-cycles. Both attacks require on the order of 21282^{128} queries in a quantum black-box model, hence our results suggest that executing these attacks may be as much as 275275 billion times more expensive than one would expect from the simple query analysis.Comment: Same as the published version to appear in the Selected Areas of Cryptography (SAC) 2016. Comments are welcome

    Criticality Aware Soft Error Mitigation in the Configuration Memory of SRAM based FPGA

    Full text link
    Efficient low complexity error correcting code(ECC) is considered as an effective technique for mitigation of multi-bit upset (MBU) in the configuration memory(CM)of static random access memory (SRAM) based Field Programmable Gate Array (FPGA) devices. Traditional multi-bit ECCs have large overhead and complex decoding circuit to correct adjacent multibit error. In this work, we propose a simple multi-bit ECC which uses Secure Hash Algorithm for error detection and parity based two dimensional Erasure Product Code for error correction. Present error mitigation techniques perform error correction in the CM without considering the criticality or the execution period of the tasks allocated in different portion of CM. In most of the cases, error correction is not done in the right instant, which sometimes either suspends normal system operation or wastes hardware resources for less critical tasks. In this paper,we advocate for a dynamic priority-based hardware scheduling algorithm which chooses the tasks for error correction based on their area, execution period and criticality. The proposed method has been validated in terms of overhead due to redundant bits, error correction time and system reliabilityComment: 6 pages, 8 figures, conferenc

    A Lyra2 FPGA Core for Lyra2REv2-Based Cryptocurrencies

    Full text link
    Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms and it is used as a proof-of-work function in several cryptocurrencies that aim to be ASIC-resistant. The most crucial hashing algorithm in the Lyra2REv2 chain is a specific instance of the general Lyra2 algorithm. In this work we present the first FPGA implementation of the aforementioned instance of Lyra2 and we explain how several properties of the algorithm can be exploited in order to optimize the design.Comment: 5 pages, to be presented at the IEEE International Symposium on Circuits and Systems (ISCAS) 201
    corecore