基于匹配的验证者-本地撤销强不可链接群签名方案

Yuto Nakazawa, T. Nakanishi
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引用次数: 1

摘要

组签名方案允许我们代表一个组匿名地对消息进行签名。用户撤销是组签名中的一个重要问题,因此目前提出了许多可撤销组签名方案。适用于组签名的应用之一是增强隐私的群体感知,其中组签名允许移动感知用户匿名身份验证以隐藏位置。在移动环境下,由于不需要用户侧的吊销列表(RL),所以适合采用验证者-本地吊销(VLR)类型的RGS方案。然而,在传统的VLR-RGS方案中,验证器中的撤销检查需要对被撤销用户的编号$R$进行$O(R)$加密操作。在此背景下,最近提出了具有有效撤销检查的VLR-RGS方案,其中撤销检查只是(位串)匹配。但是,在现有的方案中,签名与公共索引在同一时间间隔或同一任务中是可链接的。本文通过引入一个签名者在固定整数$K$的每个间隔内最多可以发出$K$签名的限制,提出了一个具有撤销令牌匹配的VLR-RGS方案。在我们的方案中,即使签名在相同的时间间隔内也是不可链接的。此外,由于使用的索引是隐藏的,因此强匿名性仍然存在。开销是撤销算法的计算成本和RL大小。我们表明,开销在群体感知用例中是实用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Strongly Unlinkable Group Signature Scheme with Matching-Based Verifier-Local Revocation for Privacy-Enhancing Crowdsensing
A group signature scheme allows us to anonymously sign a message on behalf of a group. One of important issues in the group signatures is user revocation, and thus lots of revocable group signature (RGS) schemes have been proposed so far. One of the applications suitable to the group signature is privacy-enhancing crowdsensing, where the group signature allows mobile sensing users to be anonymously authenticated to hide the location. In the mobile environment, verifier-local revocation (VLR) type of RGS schemes are suitable, since revocation list (RL) is not needed in the user side. However, in the conventional VLR-RGS schemes, the revocation check in the verifier needs $O(R)$ cryptographic operations for the number $R$ of revoked users. On this background, VLR-RGS schemes with efficient revocation check have been recently proposed, where the revocation check is just (bit-string) matching. However, in the existing schemes, signatures are linkable in the same interval or in the same task with a public index. In this paper, by introducing a limitation that at most $K$ signatures can be issued by a signer during each interval for a fixed integer $K$, we propose a VLR-RGS scheme with the revocation token matching. In our scheme, even the signatures during the same interval are unlinkable. Furthermore, since used indexes are hidden, the strong anonymity remains. The overheads are the computational costs of the revocation algorithm and the RL size. We show that the overheads are practical in use cases of crowdsensing.
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