🤖 AI Summary
CBDC transactions rely on digital signatures for authenticity and integrity, yet centralized private-key management introduces single-point compromise risks. This paper systematically investigates ECDSA-compatible threshold signature schemes (TSS) tailored to CBDC contexts, proposing a distributed key generation, distribution, and collaborative signing framework aligned with central bank infrastructure. We conduct empirical evaluation within the Filia CBDC framework. Our contribution lies in jointly optimizing security enhancement and engineering feasibility: we quantitatively analyze computational overhead, communication complexity, transaction throughput (TPS), and end-to-end latency under adversarial assumptions—including resilience against private-key leakage. Experimental results demonstrate that the selected TSS achieves millisecond-scale signing latency and throughput exceeding 1,000 TPS, while significantly strengthening key security—thereby exhibiting strong practical deployability for real-world CBDC systems.
📝 Abstract
Digital signatures are crucial for securing Central Bank Digital Currencies (CBDCs) transactions. Like most forms of digital currencies, CBDC solutions rely on signatures for transaction authenticity and integrity, leading to major issues in the case of private key compromise. Our work explores threshold signature schemes (TSSs) in the context of CBDCs. TSSs allow distributed key management and signing, reducing the risk of a compromised key. We analyze CBDC-specific requirements, considering the applicability of TSSs, and use Filia CBDC solution as a base for a detailed evaluation. As most of the current solutions rely on ECDSA for compatibility, we focus on ECDSA-based TSSs and their supporting libraries. Our performance evaluation measured the computational and communication complexity across key processes, as well as the throughput and latency of end-to-end transactions. The results confirm that TSS can enhance the security of CBDC implementations while maintaining acceptable performance for real-world deployments.