The Honey Badger of BFT Protocols

By Andrew K. Miller, Yuchong Xia, Kyle Croman, Elaine Shi, Dawn Song. Conference on Computer and Communications Security, 2016

1,005 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Information Systems

View Paper: https://www.semanticscholar.org/paper/dda1eb7aabbda6ab5ee8df31b20a7e1becb75df7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Experimental and Cognitive Psychology

In Information Systems

Citations in the corpus

SoK: Consensus in the Age of Blockchains (2017, background): “te f byzantine nodes. Thus, traditional consensus protocolscannotaccommodateopenparticipationof nodesand high churn, and are vulnerable to sybil attacks [57]. Newer BFT protocols, such as Honeybadger [104], even overcome impossibility results, and provide both safety and liveness in a fully asynchro”
RapidChain: Scaling Blockchain via Full Sharding (2018, background): “Recently, several protocols have been proposed to mitigate the performance and scalability issues of Bitcoin’s blockchain [23, 29, 41, 52, 56, 47, 32, 4, 42] using hybrid architectures that combine the open-membership nature of Bitcoin with traditional Byzantine fault tolerance [57, 19].”
All You Need is DAG (2021, methodology): “The pioneering crypto-based protocols [12, 13] were later realized in HoneyBadgerBFT, the first asynchronous Byzantine SMR system [36].”
A Survey of Distributed Consensus Protocols for Blockchain Networks (2019, methodology): “According to the performance evaluation in [16], PBFT achieves a maximum throughput of 16,000 TPS when N = 8; this figure drops to around 3,000 when N = 64.”
Monoxide: Scale out Blockchains with Asynchronous Consensus Zones (2019, background): “HoneyBadgerBFT [35] proposes an atomic broadcast protocol to optimize the communication complexity of BFT, making the asynchronous BFT to be able to support hundreds of nodes.”
A Byzantine Fault-Tolerant Ordering Service for the Hyperledger Fabric Blockchain Platform (2017, background): “, [7]), and spawned many efforts to integrate (new or existing) BFT protocols in blockchain platforms (see [3] for a survey).”
Hybrid Consensus: Efficient Consensus in the Permissionless Model (2016, methodology): “Since classical permissioned consensus [15, 19, 21, 25, 39, 40,42,45] has been studied and optimized for decades and have been shown to achieve responsiveness against 1/3 corruptions, our idea is to use a slow blockchain protocol (called snailchain) such as Nakamoto consensus [30, 46] to bootstrap f”
A scalable verification solution for blockchains (2019, background): “Proposed Byzantine “sharding” [36, 42, 47, 49, 53, 55, 57], and miner-based “serializing” [43, 60] protocols exist which aim to distribute verification work, but here we take a simple and fundamentally different approach to decouple the two tasks which miners perform, namely”
Anatomy of Threats to the Internet of Things (2019, background): “However, considerable research is being done to design and develop IoT-specific blockchain technologies that infer low computational and energy costs [188]–[191], are scalable [192], [193] and also”
SBFT: A Scalable and Decentralized Trust Infrastructure (2018, background): “Honeybadger [60] is the ﬁrst practical Byzantine fault tolerance replication system that leverages randomization to circumvent the FLP [37] impossibility.”
Security and Privacy on Blockchain (2019, background): “HoneyBadgerBFT [65] is the first practical asynchronous BFT protocol.”
From blockchain consensus back to Byzantine consensus (2017, positive): “Since then, randomisation has been extensively used to help solving consensus [11, 32, 30].”
Tendermint: Byzantine Fault Tolerance in the Age of Blockchains (2016, methodology): “Few have succeeded in putting the blockchain in context of classical consensus science until recently [102, 14, 67].”
Algorand: Scaling Byzantine Agreements for Cryptocurrencies (2017, background): “This allows Honey Badger to reach consensus within 5 minutes and achieve a throughput of 200 KBytes/sec of data appended to the ledger using 10 MByte blocks and 104 participating servers.”
Blockchain Consensus Protocols in the Wild (2017, methodology): “Without this assumption, only randomized protocols for Byzantine consensus are possible, such as the practical variations relying on distributed cryptography [20] as prototyped by SINTRA [21] or, much more recently, HoneyBadger [53].”