Cryptology ePrint Archive: Report 2021/181

Group Signatures with User-Controlled and Sequential Linkability

Jesus Diaz and Anja Lehmann

Abstract: Group signatures allow users to create signatures on behalf of a group while remaining anonymous. Such signatures are a powerful tool to realize privacy-preserving data collections, where e.g., sensors, wearables or vehicles can upload authenticated measurements into a data lake. The anonymity protects the user’s privacy yet enables basic data processing of the uploaded unlinkable information. For many applications, full anonymity is often neither desired nor useful though, and selected parts of the data must eventually be correlated after being uploaded. Current solutions of group signatures do not provide such functionality in a satisfactory way: they either rely on a trusted party to perform opening or linking of signatures, which clearly conflicts with the core privacy goal of group signatures; or require the user to decide upon the linkability of signatures before they are generated.

In this paper we propose a new variant of group signatures that provides linkability in a flexible and user-centric manner. Users – and only they – can decide before and after signature creation whether they should remain linkable or be correlated. To prevent attacks where a user omits certain signatures when a sequence of events in a certain section (e.g., time frame), should be linked, we further extend this new primitive to allow for sequential link proofs. Such proofs guarantee that the provided sequence of data is not only originating from the same signer, but also occurred in that exact order and contains all of the user’s signatures within the time frame. We formally define the desired security and privacy properties, propose a provably secure construction based on DL-related assumptions and report on a prototypical implementation of our scheme.

Category / Keywords: public-key cryptography / Privacy, Utility, User-centric security

Original Publication (with major differences): PKC 2021

Date: received 19 Feb 2021

Contact author: jdv at zurich ibm com, anja lehmann@hpi de, jesus diaz vico@gmail com

Available format(s): PDF | BibTeX Citation

Version: 20210220:173803 (All versions of this report)

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