PARIS: A Parallel RSA-Prime Inspection Tool
PARIS: A Parallel RSA-Prime Inspection Tool
复制标题
PARIS：并行 RSA-Prime 检查工具
DOI：
10.15368/theses.2013.44
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Joseph White
中科院分区：
文献类型：
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作者：
Joseph White
巴黎：PARallel RSA-prime 检查工具 Joseph White 现代计算机安全在很大程度上依赖于加密技术作为保护我们越来越依赖的数据的手段。随着互联网变得越来越普遍，安全方法必须比以往更好。可以利用验证工具来帮助增强我们对保护系统安全的方法的信心和责任感。然而，安全验证可能很困难且耗时。随着我们计算能力的提高，曾经因计算长度而被认为“困难”的计算现在可以在几分钟内完成。我们不断增加密钥的大小，并尝试使计算变得更加困难，以保护我们的信息。 “破解”难度的增加通常会带来不幸的副作用，即使验证同样困难。我们可以利用当今商用硬件（例如 GPU）所赋予的大规模并行性和计算能力来进行原本不可能执行的检查。我们的工作提供了一种实用工具，用于验证不良素数的 RSA 密钥：尽管 RSA 算法的数学健全，但这是一个导致重大安全漏洞的基本问题。 iv 我们的工具 PARIS 利用 NVIDIA 的 CUDA 框架在提供的集合中的所有键之间执行一整套最大公约数计算。我们的实现使用 GTX 480 实现了 27.5 倍的加速，使用 Tesla K20Xm 实现了 33.9 倍的加速：与少于 200000 个密钥集的参考顺序实现相比。由于运行时间减少，这种级别的加速使这种验证进入实用领域。
PARIS: A PArallel RSA-prime InSpection tool Joseph White Modern-day computer security relies heavily on cryptography as a means to protect the data that we have become increasingly reliant on. As the Internet becomes more ubiquitous, methods of security must be better than ever. Validation tools can be leveraged to help increase our confidence and accountability for methods we employ to secure our systems. Security validation, however, can be difficult and time-consuming. As our computational ability increases, calculations that were once considered " hard " due to length of computation, can now be done in minutes. We are constantly increasing the size of our keys and attempting to make computations harder to protect our information. This increase in " cracking " difficulty often has the unfortunate side-effect of making validation equally as difficult. We can leverage massive-parallelism and the computational power that is granted by today's commodity hardware such as GPUs to make checks that would otherwise be impossible to perform, attainable. Our work presents a practical tool for validating RSA keys for poor prime numbers: a fundamental problem that has led to significant security holes, despite the RSA algorithm's mathematical soundness. iv Our tool, PARIS, leverages NVIDIA's CUDA framework to perform a complete set of greatest common divisor calculations between all keys in a provided set. Our implementation offers a 27.5 times speedup using a GTX 480 and 33.9 times speedup using a Tesla K20Xm: both compared to a reference sequential implementation for sets of less than 200000 keys. This level of speedup brings this validation into the realm of practicality due to decreased runtime.