基于混沌图的新型单核并行图像加密方案

IF 2.9 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Real-Time Image Processing Pub Date : 2024-07-09 DOI:10.1007/s11554-024-01506-9

Joao Inacio Moreira Bezerra, Alexandre Molter, Gustavo Machado, Rafael Iankowski Soares, Vinícius Valduga de Almeida Camargo

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引用次数: 0

摘要

通信技术的发展加剧了人们对数据安全的担忧，使密码学的地位更加突出。图像是最广泛共享的数据之一，混沌密码引起了研究人员的极大兴趣，因为传统密码没有针对图像加密进行优化。混沌加密方案在低质量图像方面表现良好，但在全超高清图像的实时加密方面应该更快。在此背景下，我们提出了一种新型并行图像加密方案，可在 GPU 架构中执行，加密过程由单个内核组成，使其有别于之前的混沌密码和 AES。这一新贡献使我们的工作在 GeForce RTX3070 上实现了 130.8 GB/s 的吞吐量，在 Tesla V100 GPU 上实现了 251.6 GB/s 的吞吐量，与 AES 相比提高了 37%，比以前的混沌密码高出 43 倍。该密码的安全性还通过了多种攻击形式的验证。

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A novel single kernel parallel image encryption scheme based on a chaotic map

The development of communication technologies has increased concerns about data security, increasing the prominence of cryptography. Images are one of the most widely shared data, and chaotic ciphers arouse significant interest from researchers, as traditional ciphers are not optimized for image encryption. Chaotic encryption schemes perform well for low-quality images but should be faster for real-time encryption of Full Ultra HD images. In this context, a novel parallel image cipher scheme is proposed to execute in GPU architectures, where the encryption procedure consists of a single kernel, making it different from previous chaotic ciphers and the AES. This new contribution enables our work to achieve a throughput of 130.8 GB/s on a GeForce RTX3070 and 251.6 GB/s on a Tesla V100 GPU, an increase of 37% compared to the AES and 43 times higher than the previously high for chaotic ciphers. The cipher’s security is also verified regarding multiple forms of attacks.

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来源期刊

Journal of Real-Time Image Processing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

6.80

自引率

6.70%

发文量

审稿时长

6 months

期刊介绍： Due to rapid advancements in integrated circuit technology, the rich theoretical results that have been developed by the image and video processing research community are now being increasingly applied in practical systems to solve real-world image and video processing problems. Such systems involve constraints placed not only on their size, cost, and power consumption, but also on the timeliness of the image data processed. Examples of such systems are mobile phones, digital still/video/cell-phone cameras, portable media players, personal digital assistants, high-definition television, video surveillance systems, industrial visual inspection systems, medical imaging devices, vision-guided autonomous robots, spectral imaging systems, and many other real-time embedded systems. In these real-time systems, strict timing requirements demand that results are available within a certain interval of time as imposed by the application. It is often the case that an image processing algorithm is developed and proven theoretically sound, presumably with a specific application in mind, but its practical applications and the detailed steps, methodology, and trade-off analysis required to achieve its real-time performance are not fully explored, leaving these critical and usually non-trivial issues for those wishing to employ the algorithm in a real-time system. The Journal of Real-Time Image Processing is intended to bridge the gap between the theory and practice of image processing, serving the greater community of researchers, practicing engineers, and industrial professionals who deal with designing, implementing or utilizing image processing systems which must satisfy real-time design constraints.