๐ค AI Summary
This paper addresses state-machine replication under adaptive blocking attacks in client-server architectures. To tackle this problem, we propose a lightweight, fully decentralized solution. Our method comprises: (1) an asynchronous commit verification mechanism based on commitment certificates, enabling efficient client-side command execution confirmation; (2) a refined median rule from self-stabilizing consensus that eliminates leader dependence and enhances robustness against DoS attacks on critical servers; and (3) integration of command compression with threshold signatures to substantially reduce communication overhead. The protocol guarantees safety under arbitrary server blocking rates and ensures liveness when the fraction of unblocked servers exceeds a defined threshold, while also supporting rapid recovery after large-scale blocking. Theoretical analysis and experimental evaluation demonstrate near-optimal performance, strong safety guarantees, high scalability, and practical deployability.
๐ Abstract
We present a lightweight solution for state machine replication with commitment certificates. Specifically, we adapt a simple median rule from the stabilizing consensus problem [Doerr11] to operate in a client-server setting where arbitrary servers may be blocked adaptively based on past system information. We further extend our protocol by compressing information about committed commands, thus keeping the protocol lightweight, while still enabling clients to easily prove that their commands have indeed been committed on the shared state. Our approach guarantees liveness as long as at most a constant fraction of servers are blocked, ensures safety under any number of blocked servers, and supports fast recovery from massive blocking attacks. In addition to offering near-optimal performance in several respects, our method is fully decentralized, unlike other near-optimal solutions that rely on leaders. In particular, our solution is robust against adversaries that target key servers (which captures insider-based denial-of-service attacks), whereas leader-based approaches fail under such a blocking model.