Abstract During the last years, several card-based Zero-Knowledge Proof (ZKP) protocols for Nikoli’s puzzles have been designed. Although there are relatively simple card-based ZKP protocols for a number of puzzles, such as Sudoku and Kakuro, some puzzles face difficulties in designing simple protocols. For example, Slitherlink requires novel and elaborate techniques to construct a protocol. In this study, we focus on three Nikoli puzzles: Nurikabe, Hitori, and Heyawake. To date, no card-based ZKP protocol for these puzzles has been developed, partially because they have a relatively tricky rule that colored cells should form a connected area (namely a polyomino); this rule, sometimes referred to as “Bundan-kin” (in Japanese), complicates the puzzles, as well as facilitating difficulties in designing card-based ZKP protocols. We address this challenging task and propose a method for verifying the connectivity of hidden colored cells in a ZKP manner, such that we construct card-based ZKP protocols for the three puzzles.
Know Your Customer (KYC) is a costly and heavily regulated process that financial institutions are legally required to undertake to conduct business with their customers. Distributed Ledger Technology (DLT) can be used as a coordination mechanism for financial institutions to share KYC costs in a common jurisdiction. Previous techniques that use DLT to support the KYC process, perhaps unexpectedly, introduce a single point of failure in the system. Indeed, financial institutions are vulnerable to repercussions if a single institution makes an operational mistake during the onboarding stage. We tackle this problem by introducing a probabilistic mechanism, where some of the financial institutions involved need to independently repeat the KYC process in the form of a randomised audit. This novel approach mitigates the single point of failure of the previous DLT-based KYC designs and introduces a natural trade-off between the security of the KYC process and its cost efficiency. In our approach the audit probability can be either set as a global DLT parameter or be dependent on attributes associated with the particular client.
Mathematics, Computing, and Information Processing