BigDipper: Sharded Censorship Resistant Data Availability for Leader-Based BFT
This work addresses the problem of transaction censorship in leader-based BFT protocols for time-sensitive applications like auctions and liquidations, offering a flexible, end-to-end approach.
BigDipper introduces a censorship-resistant data availability layer (DA-CR) for leader-based BFT protocols, enabling higher-layer protocols to choose their own protection levels without forcing all transactions into a fixed policy. The design keeps data sharded on the critical path, with validators checking only commitments and availability evidence, and is instantiated in HotStuff-2.
Leader-based Byzantine-fault-tolerant (BFT) protocols provide low latency and simple communication structure, but they give the leader short-term control over transaction inclusion. A malicious leader can keep the protocol live while delaying or excluding time-sensitive transactions such as auction bids, oracle updates, liquidations, and bridge messages. Existing responses often build a fixed censorship-resistance, hiding, or ordering mechanism into the protocol path, forcing all transactions to pay for the same protection level. name follows the end-to-end principle: the consensus layer exposes inclusion primitives rather than hardcoding stronger policies. Higher-layer protocols can then choose their own submission strategies and resources, whether through replication, erasure coding, or other mechanisms, to obtain the censorship-resistance, hiding, ordering, or execution guarantees they need. At the core of BigDipper is censorship-resistant data availability, or DA-CR, which certifies available replica-contributed mini-blocks for use by leader-based consensus. A central design goal is that data remains sharded on the consensus critical path: validators do not reconstruct or execute the full payload before voting, but instead check commitments, availability evidence, and the DA-CR inclusion rule. We define DA-CR guarantees for data-tampering resistance, honest mini-block inclusion, and residual leader influence. We then give concrete constructions based on erasure coding and linear commitments, analyze client-tunable transaction submission, and instantiate BigDipper inside HotStuff-2.