Data mining entails the discovery of unexpected but reusable knowledge from large unorganized datasets. Among the many available data-mining algorithms, association rule mining (ARM) is very common. It was developed to aggregate all data into one site and subsequently mine them. In recent years, organizations in different fields have been required to collaborate to create new value. However, data mining among and within organizations has raised privacy and confidentiality concerns. In our scheme, parties cannot share anything other than the number of records, including the candidate itemset. This study focuses on the private-set intersection instead of the scalar product and shows that this intersection enables organizations to execute ARM on vertically partitioned data, allowing flexible information sharing while preserving privacy without increasing communication and computation costs. Furthermore, we focus on the fact that the number of protocol rounds among parties can be reduced and present three use cases in which the proposed scheme works more effectively than the existing schemes.

This paper proposes a model for account-holding proofs across multiple authorities and presents a concrete construction from JWT-derived evidence, enabling a verifier to evaluate the resulting artifact under specified system assumptions and acceptance policies. Conventional account linkage approaches often depend on particular identity providers (IdPs) or linkage mechanisms and may expose or correlate more credential information than is necessary for the verifier’s policy. To address this, we formalize a scheme-agnostic abstract model and organize its security, disclosure-related, and deployment requirements. As a concrete instantiation, we apply an RSA-based synchronized aggregate signature scheme to encoded messages derived from the RS256 preprocessing step of JWT signing inputs. The resulting artifact is not a standard JWT and is not intended for direct verification by existing JWT/OIDC verifiers; rather, it provides a single aggregate signature component over multiple JWT-derived evidence items. Through analytical and prototype-based evaluation, we show that the signature-component data to be presented is reduced from n individual components to a single aggregate component and that the exponentiation applied to the presented signature component is reduced from $O\left(n\right)$ to $O\left(1\right)$, while the overall verification remains dominated by per-message public-key terms. The results of prototype implementation indicate that aggregate verification is not faster than ordinary RS256 JWT verification under the evaluated parameters; therefore, the construction is better suited to one-time or low-frequency account-holding proof scenarios in which the additional latency is tolerable.

The proliferation of coronavirus disease (COVID-19) has prompted changes in business models. To ensure a successful transition to non-face-to-face and electronic communication, the authenticity of data and the trustworthiness of communication partners are essential. Trust services provide a mechanism for preventing data falsification and spoofing. To develop a trust service, the characteristics of the service and the scope of its use need to be determined, and the relevant legal systems must be investigated. Preparing a document to meet trust service provider requirements may incur significant expenses. This study focuses on electronic signatures, proposes criteria for classification, classifies actual documents based on these criteria, and opens a discussion. A case study illustrates how trusted service providers search a document highlighting areas that require approval. The classification table in this paper may prove advantageous at the outset when business decisions are uncertain, and there is no clear starting point.