Conference Paper

CryptoGraphics: Secret Key Cryptography Using Graphics Cards

DOI: 10.1007/978-3-540-30574-3_23 Conference: Topics in Cryptology - CT-RSA 2005, The Cryptographers' Track at the RSA Conference 2005, San Francisco, CA, USA, February 14-18, 2005, Proceedings
Source: DBLP


We study the feasibility of using Graphics Processing Units (GPUs) for cryptographic processing, by exploiting the ability for GPUs to simultaneously process large quantities of pixels, to offload symmetric key encryption from the main processor. We demonstrate the use of GPUs for applying the key stream when using stream ciphers. We also investigate the use of GPUs for block ciphers, discuss operations that make certain ciphers unsuitable for use with a GPU, and compare the performance of an OpenGL-based implementation of AES with implementations utilizing general CPUs. While we conclude that existing symmetric key ciphers are not suitable for implementation within a GPU given present APIs, we discuss the applicability of moving encryption and decryption into the GPU to image processing, including the handling of displays in thin-client applications and streaming video, in scenarios in which it is desired to limit exposure of the plaintext to within the GPU on untrusted clients.

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    • "According to design of FPGA, performance of encryption request at hardware is calculated. According to analysis mentioned in [4], [5] [7], [8], [9], [10] "
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    ABSTRACT: Cryptographic transformations are a fundamental building block in many security applications and protocols. To improve performance, several vendors market hardware accelerator cards. However, until now no operating system provided a mechanism that allowed both uniform and efficient use of this new type of resource. We have implemented the operating system service in Windows environment as Scheduler which automatically starts when operating system boots. As system always gives priority to hardware, kernel and applications in order, we have designed the scheduler which schedules the encryption requests at hardware, kernel and application level respectively. When request for encryption comes to scheduler, it schedules the requests at hardware, kernel and application level services in order and also according to availability. It is proved that the scheduler is able to save CPU utilization by scheduling the encryption request for AES, RSA and SHA1 at three levels. It is also proved that the developed system is reliable in case of any failure in hardware, as it proceeds by scheduling the load at kernel and application level processes. It also proved that the performance of AES is very fast at hardware level, performance of SHA1 is uniform at all three levels comparatively and performance of RSA is very low at application and kernel level as compared to AES and SHA1.
    International Conference on Advances in Communication, Network and Computing (CNC 2013), Chennai; 02/2013
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    • "In addition to the special registers, implementers have considered other attached hardware for cryptographic use. For example, some display adapters possess considerable computing power, although implementers have had mixed success in adapting their instruction set and interface for cryptographic use [33] [16]. Hardware targeted to cryptography has usually been an add-on, but the recent UltraSPARC T2 from Sun Microsystems may be a harbinger of widespread onchip cryptographic hardware on common systems. "
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    ABSTRACT: This chapter describes and compares the software implemen-tation of popular elliptic curve pairings on two architectures, of which the Intel Pentium 4 and Core2 are representatives.
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    • "At the time, performance of the algorithm was not as impressive as it would be today using current GPU hardware, with the FFT algorithm running slightly slower on the GPU compared to optimized FFT algorithms running on CPU's. Since Moreland and Angel's foray into general purpose computing on GPU's, these devices have been leveraged to investigate molecular dynamics [2] [3], incompressible flows [4], N-body potential problems [5], optical flow techniques [6], unsteady turbulent flows [7], helicopter rotor wake modeling [8], aerodynamic coefficient prediction [9], cryptography [10], and even new computer anti-virus systems [11] [12], as well as many other areas. For many applications, researchers have demonstrated that computational speed-ups can be significant. "
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