Exigences de paiement pour les monnaies numériques de banques centrales

Abstract

The strong interest in central bank digital currencies (CBDCs) arises in a context of increased digitization of payments and a growing search for more resilient and inclusive solutions. Among the desired features of CBDCs, offline payment constitutes a central challenge. It ensures the resilience of payment systems, promotes financial inclusion, and guarantees transaction continuity in the absence of network connectivity. However, unlikeonline payments, offline payments for CBDCs impose specific constraints and sometimes conflicting requirements in terms of security, privacy, fraud prevention, auditability, and integration with existing infrastructures. Consequently, this thesis focuses on the anal ysis and formalization of these offline payment requirements, as well as on the study of technical solutions capable of addressing them in a coherent manner. Accordingly, basedon this analysis leading to a structured taxonomy, the thesis introduces several original frameworks illustrating different strategies for satisfying these requirements. The first framework, PrivTEE-Pay, relies on a single-ledger architecture and exploits trusted execution environments combined with cryptographic primitives such as blind signatures and zero-knowledge proofs (zk-SNARKs). The second framework extends a conventionalpayment architecture through the integration of a secure smart card, the DigiVault card, coupled with a smartphone. This combined approach also relies on privacy-enhancing technologies and on the fraud detection model MarkoPayChain, based on Markov chains. A third framework, Block-PAD, proposes a hybrid architecture combining a central ledger for monetary issuance and a blockchain for delayed synchronization of offline transactions.Finally, the thesis complements these contributions with an advanced offline fraud detection framework, based on a combination of expert rules, explainable machine learning models, and hidden Markov chains. Moreover, these different frameworks are experimentally evaluated using simulators and synthetic datasets dedicated to offline CBDC payments. The results show that the proposed solutions make it possible to address the requirements identified in the taxonomy, each through explicit trade-offs. This thesis thus provides concrete contributions to the design of resilient, secure, performant, auditable, and privacy-preserving offline CBDC payment systems that can integrate into existing payment infrastructures.