Implementation of high speed hash function Keccak on GPU

Abstract

Nowadays, a hash function is used for password management. The hash function is desired to possess the following three characteristics: Pre-Image Resistance, Second Pre-Image Resistance, and Collision Resistance. They are set on the assumption that it is computationally difficult to find the original message from a given hash value. However, the security level of the password management will be further reduced by implementing a high speed hash function on GPU. In this paper, the implementation of high speed hash function Keccak-512 using the integrated development environment CUDA for GPU is proposed. The following four techniques are used in order to speed up its implementation. The first one is reforming lookup tables from 2 dimensional arrays to 1 dimensional arrays at step ρ and π. The second is an investigation into the effect of using constant memory and shared memory for constant values. The third is the finding out the optimal configuration of blocks-threads, then evaluate the implementation according to the occupancy. And the last one is using CUDA streams with overlapping to hide the overhead of data transfer and GPU processing. As the result, the throughput of implemented Keccak on GeForce GTX 1080 achieved up to maximum 64.58 GB/s. It is about 14.0 times faster than the previous research result. In addition, the safety level of Keccak is also discussed at the point of Pre-Image Resistance especially. In order to implement a high speed hash function for password cracking, we developed a special program for passwords up to 71 characters. Moreover, the throughputs of 2 times as well as 3 times hash are also evaluated. It is proved that multiple times hash is possible to greatly improved the security level of Keccak with password management. The throughput of hashing password with a large number of iterations confirmed the effect was about 90%. That is the time required to hash one password for 1000 times was almost the same as the total time to sequentially hash 900 passwords.

Fast Implementation of SHA-3 in GPU Environment

“…In this section, we present the SHA-3 performance results using CUDA Stream. A previous work by Dat et al showed a throughput of up to 64.58 Gb/s using three CUDA streams [24]. We present the results of SHA-3 implementation in GTX 1070 and RTX 2080Ti architecture environments.…”

“…In this paper, we proposed an effective parallel message copy of input data and kernel execution methods by applying CUDA stream and we provided the result of SHA-3 implementation using CUDA stream. Also, in SHA-3 implementation, performance using CUDA stream, we present the result of comparing Dat et al's proposal and our implementation [22], [24]. Our optimized implementation of SHA-3 using 3 CUDA streams provides the maximum throughput of 95.67Gb/s in a GTX 1070 environment.…”

“…We customized the optimization method of Dat et al to our implementation. In addition, Dat et al extended their optimal methods using three CUDA streams in [24].…”

Parallel Implementation of Lightweight Secure Hash Algorithm on CPU and GPU Environments

“…In addition, research on ECC using GPU architecture is continuously being conducted [31][32][33]. Research on block cipher algorithms and hash functions in GPU architectures has also been published [34][35][36][37][38][39][40][41]. However, there are no studies of hash functions using AVX-512 and LSH optimization research implementation using GPUs.…”

High-performance FPGA implementation of the secure hash algorithm 3 for single and multi-message processing

“…During and after the NIST's competition several implementations of SHA-3 are presented [8]- [17], [18]. In spite of the availability of software implementations of security algorithms using high powerful central processing unit (CPUs) [19], hardware implementations of these algorithms using high developed platforms such as fieldprogrammable gate arrays (FPGAs) and application specific integrated circuit (ASICs) remains greatly demanded.…”