High-speed implementation of rainbow table method on heterogeneous multi-device architecture

Li, Pei; Zhu, Wenwu; Chen, Jiageng; Yao, Shixiong; Hsu, Ching-Fang; Xiong, Guangquan

doi:10.1016/j.future.2023.01.022

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…The acceleration ratios for the precomputation phase were 2.03 times and 131.3 times, respectively. Meanwhile, the acceleration ratios for the online phase were 1.97 times and 1.44 times, respectively [15].…”

Section: Cpu-gpu Heterogeneous Platformmentioning

confidence: 99%

A review of time-memory trade-off techniques

Teng

2024

ACE

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This paper delves into the discussion of time-memory trade-off techniques in the field of cryptanalysis. The method was initially introduced by Hellman in 1980, subsequently, DP trade-off, rainbow trade-off, and checkpoint trade-off have been proposed to enhance the efficiency of cryptographic attacks. This paper elaborates on the concept of rainbow trade-off and their variants and presents optimizations in terms of storage and runtime speed for time-memory trade--off methods. Ingenious storage optimization significantly reduces the storage overhead of pre-computed tables, and the rapid advancement of implementation platforms achieves speed optimization for the online phase. Through these optimization measures, time-memory trade-off methods exhibit even more remarkable performance in practical applications. For researchers and practitioners in the field of cryptography, the content of this paper provides valuable references and insights for their work.

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Section: Cpu-gpu Heterogeneous Platformmentioning

confidence: 99%

A review of time-memory trade-off techniques

Teng

2024

ACE

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“…This section examines the effect of a flexible, highperformance, and low-power cryptographic hashing processor on blockchain-based IoT applications as follows High flexibility: The rapidly expanding field of cryptographic applications demands a flexible cryptographic hashing processor capable of supporting a diverse array of hash functions to ensure network security and data integrity. For instance, SHA-256 is commonly employed in password encryption, while BLAKE-256 and BLAKE2s are utilized for cryptographic key generation in biomedical image encryption and message authentication, respectively, in IoT and heterogeneous systems [24], [26]. Furthermore, diverse hash functions such as double SHA-256, Blake-256, and Scrypt are employed in different mining processes of different blockchain networks, such as Bitcoin, Decred, and Litecoin, respectively [5], [6], [11].…”

Section: Importance Of Flexible High-performance and Low-power Crypto...mentioning

confidence: 99%

Flexible and Energy-Efficient Crypto-Processor for Arbitrary Input Length Processing in Blockchain-Based IoT Applications

LE,

PHAM,

TRAN

et al. 2024

IEICE Trans. Fundamentals

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Blockchain-based Internet of Things (IoT) applications require flexible, fast, and low-power hashing hardware to ensure IoT data integrity and maintain blockchain network confidentiality. However, existing hashing hardware poses challenges in achieving high performance and low power and limits flexibility to compute multiple hash functions with different message lengths. This paper introduces the flexible and energyefficient crypto-processor (FECP) to achieve high flexibility, high speed, and low power with high hardware efficiency for blockchain-based IoT applications. To achieve these goals, three new techniques are proposed, namely the crypto arithmetic logic unit (Crypto-ALU), dual buffering extension (DBE), and local data memory (LDM) scheduler. The experiments on ASIC show that the FECP can perform various hash functions with a power consumption of 0.239-0.676 W, a throughput of 10.2-3.35 Gbps, energy efficiency of 4.44-14.01 Gbps/W, and support up to 8916-bit message input. Compared to state-of-art works, the proposed FECP is 1.65-4.49 times, 1.73-21.19 times, and 1.48-17.58 times better in throughput, energy efficiency, and energy-delay product (EDP), respectively.

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High-speed implementation of rainbow table method on heterogeneous multi-device architecture

Cited by 2 publications

References 9 publications

A review of time-memory trade-off techniques

A review of time-memory trade-off techniques

Flexible and Energy-Efficient Crypto-Processor for Arbitrary Input Length Processing in Blockchain-Based IoT Applications

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