13-th IEEE International Conference on Peer-to-Peer Computing Information Propagation in the Bitcoin Network

Citations in the corpus

• Wireless Network Intelligence at the Edge (2018, background): “The reliability and scalability of FL can further be improved by adopting blockchain [211], [212], as exemplified by block-chained FL (BlockFL) in our preliminary study [172].”
• Zerocash: Decentralized Anonymous Payments from Bitcoin (2014, methodology): “Recent research [17] suggests that the Bitcoin”
• Blockchain's adoption in IoT: The challenges, and a way forward (2019, background): “As per experimental results, Honeybadger-BFT provides better throughput in terms of TPS, than PBFT.495 However, it has been tested for the tolerance of up to f = n/4 faulty nodes only.”
• Performance Analysis of Private Blockchain Platforms in Varying Workloads (2017, methodology): “Earlier studies often use bitcoin as a study case for insight analysis such as the relationship between propagation delay and blockchain forks [4].”
• Inclusive Block Chain Protocols (2015, background): “Previous work [6, 12] has shown that with increasing block sizes (or equivalently with increasing block creation rates), more stale (off-chain) blocks are created.”
• Optimal Selfish Mining Strategies in Bitcoin (2015, background): “Additional analysis of block creation in the presence of delays and its effects on throughput and double spending appears in [17,13,7].”
• Blockchain-Based Dynamic Key Management for Heterogeneous Intelligent Transportation Systems (2017, background): “Another issue of blockchain approach is the use of transactions which conveys information among the distributed network and can hence send messages using peer-to-peer mode [27].”
• A Survey of Distributed Consensus Protocols for Blockchain Networks (2019, background): “Meanwhile, a shorter block interval yields higher transaction throughput but also leads to higher risk of 51%-attack [73].”
• Secure High-Rate Transaction Processing in Bitcoin (2015, methodology): “The relation between the block size and the time it took to reach 25% (red), 50% (green), and 75% (blue) of monitored nodes, based on data provided by Decker and Wattenhofer [7].”
• Towards Scaling Blockchain Systems via Sharding (2018, result): “sing the valid blocks. We also observe that a larger block size leads to a higher stale block rate, and as a consequence, a lower throughput. This nding is in line with performance of Bitcoin network [20, 27], wherein larger block size means higher probability of forks and stale blocks. Discussion. ”
• Incentivizing Consensus Propagation in Proof-of-Stake Based Consortium Blockchain Networks (2019, background): “Recruiting more verifiers can avoid centralized block verification and decrease impacts of compromised verifiers leading to more reliable and secure blockchain network [1], [5].”
• Hybrid Consensus: Efficient Consensus in the Permissionless Model (2016, methodology): “[47] show, for a realistic network delay bound ∆ = 10 seconds as suggested by measurement studies [21], a 10-minute block interval is necessary to resist a 49.”
• Permacoin: Repurposing Bitcoin Work for Data Preservation (2014, background): “An estimated 2% of produced blocks are stale in Bitcoin [9].”
• Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies (2016, methodology): “In order to mitigate the threat, [Decker and Wattenhofer 2013] propose a modified message exchange behavior.”
• Erays: Reverse Engineering Ethereum's Opaque Smart Contracts (2018, background): “, gambling or trading) [34] and measuring the performance of the underlying peer-to-peer network [19, 20, 36, 37].”
• Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack (2016, background): “We are therefore primarily interested in studying the steady state ratio of blocks in the main chain mined by Alice or Bob, as this ultimately reflects the revenue (i.e., in dollars per day) to each party.”