🤖 AI Summary
This work addresses the challenge of securely excluding historical updates from compromised nodes in traditional Byzantine fault-tolerant CRDTs without violating causal consistency. The authors propose a fine-grained trust model that, for the first time in Byzantine CRDTs, decouples identity trust from content trust. By integrating deterministic reconstruction, public-key-based identity verification, and a semantics-aware update filtering mechanism, the approach enables selective inclusion or exclusion of updates. This design supports application-level policies and effectively mitigates Byzantine behavior and faulty nodes while strictly preserving causal consistency, thereby significantly enhancing the robustness and flexibility of decentralized systems in post-compromise scenarios.
📝 Abstract
Conflict-free Replicated Data Types (CRDTs) provide strong eventual consistency without coordination, but classical approaches assume benign participants. In Byzantine settings, convergence is typically enforced through agreement on update validity, often relying on identity-based filtering. However, such approaches struggle in post-compromise scenarios, where a previously correct participant becomes malicious: retroactive exclusion of its updates may break causal dependencies and invalidate subsequent computations. In this paper, we decouple identity-based trust from content-based trust and introduce a fine-grained trust model that combines both dimensions. Building on deterministic reconstruction, our approach allows replicas to preserve previously accepted updates while enabling selective inclusion or exclusion based on both the originating identity (e.g., public keys) and the semantics of individual updates. Trust decisions can incorporate application-level policies, enabling precise control over the impact of each update on the system state. Our approach preserves causal consistency and enables robust and flexible handling of both Byzantine and faulty behavior in decentralized CRDT systems.