Accelerating SSL with GPUs

JangKeon,; HanSangjin,; HanSeungyeop,; Moon, Sue; ParkKyoungSoo,

doi:10.1145/1925861.1925885

Cited by 8 publications

(8 citation statements)

References 2 publications

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“…As mentioned before, the first paper using CUDA to parallelize AES on GPU is finally used to accelerate encrypting of the data of OpenSSL applications. Besides, Jang et al implemented a parallel SSL on a GPU, including AES, RSA, and HMAC‐SHA1, and obtained the speed of 21.5K SSL transactions per second. Moreover, in database applications, Fazackerley et al implemented Cypher Block Chained parallel AES on GPU.…”

Section: Related Workmentioning

confidence: 99%

Practical parallel AES algorithms on cloud for massive users and their performance evaluation

Fei

et al. 2015

Concurrency and Computation

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Summary Many e‐business or social network servers have been constructed on cloud. On such open environments, private data of massive users have to be protected by encrypting, such as using Advanced Encryption Standard (AES), and furthermore, this process must be finished in a short time for users' better experience. This gives huge pressure on cloud servers, especially common servers, such as web servers. We urgently need an inexpensive and highly efficient method to relieve cloud servers' pressure. Fortunately, many cores of a graphics processing unit (GPU) can undertake this hard mission because of stronger computing power and lower price. The GPU environments can be virtualized on demand by cloud through the vCUDA technology. Of course, for those clouds not equipped with a GPU, a central processing unit (CPU) can still work as multithreads in parallel. Thus, in a cloud, AES can be parallelized using many cores of a GPU or multicores of a CPU with high efficiency and low cost. For typical cloud applications, such as web services, there are massive users and each one has short plaintext. If we simply parallelize AES in such an application, we cannot obtain better performance because of the GPU's extra data transferring cost. Thus, we coalesce the massive users' data and cut these data into same‐length slices for improving the performance of parallel AES as much as possible. So we design six parallel AES algorithms using GPU parallelism or CPU parallelism, which differ in parallel scope and whether data are coalesced or cut to slices. Specifically, they are coalescent and sliced GPU (GCS), coalescent and unsliced GPU, uncoalescent GPU, coalescent and sliced CPU, coalescent and unsliced CPU, and uncoalescent CPU. Moreover, we implement them on two representative platforms and evaluate their performance. Through comparing their performance, GCS has the best performance among these algorithms. In a cloud with Nvidia GPUs, GCS is a more powerful algorithm for massive users' data encrypting, relatively. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Related Workmentioning

confidence: 99%

Practical parallel AES algorithms on cloud for massive users and their performance evaluation

Fei

et al. 2015

Concurrency and Computation

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“…The birth and development of the GPU technology, can be divided into Ex-GPU era, fixed function pipeline era, programmable shader pipeline era and unified programmable shaders era. In November 2006, the NVIDIA company released G80-parallel-programming-model and C-language-based development environment-CUDA (Compute Unified Device Architecture) [3].…”

Section: Traditionalmentioning

confidence: 99%

Comparison and Analysis of GPGPU and Parallel Computing on Multi-Core CPU

Zhang¹,

Zhang²,

Bi³

2012

IJIET

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“…There is a relatively low uptake on the use of TLS/SSL, mainly due to the associated performance overhead. A high end CPU core can handle approximately 1,000 HTTPS transactions per second with 1,024-bit RSA while the same core can handle 10,000 plain HTTP transactions per second (Jang et al, 2010). The most expensive performance cost in TLS/SSL is the RSA computations (Coarfa et al, 2006).…”

Section: Web Service Securitymentioning

confidence: 99%

“…The most expensive performance cost in TLS/SSL is the RSA computations (Coarfa et al, 2006). Performance improvements can be gained by using Graphics Performance Units (GPUs) to handle the RSA throughput (Jang et al, 2010) but this is still in the initial research stages. The performance overhead associated with TLS/SSL is still far lower than with WS-Security.…”

Section: Web Service Securitymentioning

confidence: 99%

WS-I* compliant web service SOAP message security performance

McHale

O'Raw

Curran

2012

IJWS

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The OASIS web services security (WSS) standard has been developed to provide encryption and digital signing for SOAP messaging to ensure the information in the message is confidential and that the sender and receiver are who they say they are. It has also introduced interoperability and performance problems. Interoperability has been improved with the introduction of the WS-I* Basic and Basic Security Profiles. New web stacks such as Apache CXF have attempted to address performance issues. The purpose of this research is to investigate the performance impacts of securing WS-I* compliant SOAP messages when using the Apache CXF web service framework. We measured the performance impact of WS-Security and WS-SecureConversation under different conditions and using various WS-I* compliant cryptographic algorithms. We found that WS-SecureConversation is the better option when sending a large number of messages but for a small number of large messages WS-Security can sometimes be the better option.

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Accelerating SSL with GPUs

Cited by 8 publications

References 2 publications

Practical parallel AES algorithms on cloud for massive users and their performance evaluation

Practical parallel AES algorithms on cloud for massive users and their performance evaluation

Comparison and Analysis of GPGPU and Parallel Computing on Multi-Core CPU

WS-I* compliant web service SOAP message security performance

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