Hybrid Consensus: Efficient Consensus in the Permissionless Model
By Rafael Pass, Elaine Shi. International Symposium on Distributed Computing, 2016
416 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/16578ec325c1139c85d35ace62d265420f1ae72f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Dusist Niyato
- Mariana Raykova
- Zibin Zheng
- Aviv Zohar
- Dan Boneh
- Beng Chin Ooi
- Tien Tuan Anh Dinh
- Zehui Xiong
In Computer Networks and Communications
- Zibin Zheng
- Aviv Zohar
- Huawei Huang
- Jing Bian
- Q. Zhou
- Dusist Niyato
- Yonatan Sompolinsky
- Yoad Lewenberg
In Information Systems
- Aviv Zohar
- Dusist Niyato
- Zibin Zheng
- Yonatan Sompolinsky
- Zehui Xiong
- Robbert van Renesse
- Yoad Lewenberg
- Ittay Eyal
Citations in the corpus
- REM: Resource-Efficient Mining for Blockchains (2017, background): “These works, and the line of hybrid blockchain systems starting with Bitcoin-NG [36, 57, 68], can all utilize PoUW as a low-waste alternative to PoW.”
- OmniLedger: A Secure, Scale-Out, Decentralized Ledger via Sharding (2018, methodology): “To choose representative validators via proof-of-work, Om-niLedger builds on ByzCoin [32] and Hybrid Consensus [38], using a sliding window of recent proof-of-work block miners as its validator set.”
- Solutions to Scalability of Blockchain: A Survey (2020, background): “Later works such as Hybrid consensus [72], Solidus [73] also propose to combine different protocols with PoW”
- RapidChain: Scaling Blockchain via Full Sharding (2018, background): “Hybrid Consensus [56] proposes to periodically select a committee that runs a Byzantine consensus protocol assuming a slowly-adaptive adversary that can only corrupt honest nodes in certain periods of time.”
- A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks (2018, methodology): “Following the methodology of [153], hybrid consensus mechanisms atop Nakamoto protocols are proposed in [155] and [156] with the goal of providing strong consistency and immediate finality.”
- SBFT: A Scalable and Decentralized Trust Infrastructure (2018, background): “Several recent proposals [11], [39], [43], [59], [63] explore the idea of building distributed ledgers that elect a committee (potentially of a few tens or hundreds of nodes) from a large pool of nodes (potentially thousands or more) and have this smaller committee run a Byzantine fault tolerant…”
- Algorand: Scaling Byzantine Agreements for Cryptocurrencies (2017, methodology): “Pass and Shi’s paper [42] acknowledges that the Hybrid consensus design is secure only with respect to a “mildly adaptive” adversary that cannot compromise the selected servers within a day (the participant selection interval), and explicitly calls out the open problem of handling fully adaptive adv”
- Proof-of-Stake Consensus Mechanisms for Future Blockchain Networks: Fundamentals, Applications and Opportunities (2019, methodology): “Different from the Hybrid Consensus protocol [20], the committee is responsible for both transaction adding and block confirmation in the Peercensus protocol.”
- SPECTRE: A Fast and Scalable Cryptocurrency Protocol (2016, background): “The work of Pass and Shi [16] constructs an interesting hybrid model that combines consensus protocols, building on a previous work by [12, 2].”
- BLOCKBENCH: A Framework for Analyzing Private Blockchains (2017, background): “For example, eclipse attack [30] exploits the application-level protocol to surround the targeted nodes with ones under the attacker’s control.”
- 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”
- Monoxide: Scale out Blockchains with Asynchronous Consensus Zones (2019, critical): “For example, Algorand is susceptible to bias in the randomness of the variable random function (VRF) invocation [20], while ByzCoin may not reach the agreement on the committee election, as reported in the hybrid consensus system [38].”