Secure Conformance Checking using Token-based Replay and Homomorphic Encryption

Computer Science > Cryptography and Security [Submitted on 28 Apr 2026] Secure Conformance Checking using Token-based Replay and Homomorphic Encryption Luis-Armando Rodríguez-Flores, Luciano García-Bañuelos, Abel Armas-Cervantes, Astrid-Monserrat Rivera-Partida Conformance checking, one of the main process mining operations, aims to identify discrepancies between a process model and an event log. The model represents the expected behaviour, whereas the event log represents the actual process behaviour as captured in information systems' records. Traditionally, the process model and the event log are both accessible to the business analyst performing the conformance checking. However, in some contexts the log's owner may want to protect critical or sensitive information in the log and still check its conformance with respect to a model belonging to another party. In this paper, we propose a secure approach to conformance checking based on the well-known token-based replay algorithm and homomorphic encryption. An evaluation is performed using a synthetic log, showing the practicality of the proposed technique. Comments: 18 pages Subjects: Cryptography and Security (cs.CR); Software Engineering (cs.SE) Report number: ITESMPUE-26-02 Cite as: arXiv:2604.25190 [cs.CR]   (or arXiv:2604.25190v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.25190 Focus to learn more Submission history From: Luciano García-Bañuelos [view email] [v1] Tue, 28 Apr 2026 03:53:36 UTC (166 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.SE References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)