Verification of a Batch of Bad Signatures by Using the Matrix-Detection Algorithm

Yi-Li Huang, Chu-Hsing Lin, Fang-Yie Leu
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引用次数: 3

Abstract

Batch verification is a method devised to verify multiple signatures as a whole simultaneously. In literatures, we can see that some conventional batch verification schemes cannot effectively and efficiently identity bad signatures. Small Exponent test, a popular batch verification method, has its own problems, e.g., after a test, bad signatures still exist with some escape probabilities. In this paper, we propose a batch verification approach, called Matrix-Detection Algorithm (MDA for short), with which when a batch of signatures has less than four bad signatures or odd number of bad signatures, all bad signatures can be identified. Given 1024 signatures with 4 bad signatures, the maximum escape probability pmax of the MDA is 5.3×10-5 , and max p decreases as digital signatures or bad signatures increase. Analytic results show that the MDA is more secure and efficient than the SET.
利用矩阵检测算法验证一批不良签名
批验证是将多个签名作为一个整体同时进行验证的一种方法。在文献中,我们可以看到一些传统的批验证方案不能有效和高效地识别坏签名。小指数测试是一种流行的批处理验证方法,但它也有自己的问题,例如,在测试后,仍然存在不良签名并有一定的逃逸概率。本文提出了一种批验证方法,即矩阵检测算法(Matrix-Detection Algorithm,简称MDA),当一批签名的坏签名个数小于4个或奇数个时,可以识别出所有的坏签名。在1024个签名和4个坏签名的情况下,MDA的最大逃逸概率pmax为5.3×10-5, max p随着数字签名或坏签名的增加而减小。分析结果表明,MDA比SET更安全、更高效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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