most citedProof of Federated Learning: A Novel Energy-recycling Consensus Algorithm

13 citations · 15 across the 4 of their papers we have counts for

collaborators

6 papers

cs.GT2020

Privacy-aware Data Trading

Shengling Wang, Lina Shi, Junshan Zhang +2

The growing threat of personal data breach in data trading pinpoints an urgent need to develop countermeasures for preserving individual privacy. The state-of-the-art work either e…

cs.GT2020

A Misreport- and Collusion-Proof Crowdsourcing Mechanism without Quality Verification

Kun Li, Shengling Wang, Xiuzhen Cheng +1

Quality control plays a critical role in crowdsourcing. The state-of-the-art work is not suitable for large-scale crowdsourcing applications, since it is a long haul for the reques…

cs.GT2020

Egoistic Incentives Based on Zero-Determinant Alliances for Large-Scale Systems

Shengling Wang, Peizi Ma, Qin Hu +2

Social dilemmas exist in various fields and give rise to the so-called free-riding problem, leading to collective fiascos. The difficulty of tracking individual behaviors makes ego…

cs.CR201913 cited

Proof of Federated Learning: A Novel Energy-recycling Consensus Algorithm

Xidi Qu, Shengling Wang, Qin Hu +1

Proof of work (PoW), the most popular consensus mechanism for Blockchain, requires ridiculously large amounts of energy but without any useful outcome beyond determining accounting…

cs.GT20191 cited

An Uncertainty- and Collusion-Proof Voting Consensus Mechanism in Blockchain

Shengling Wang, Xidi Qu, Qin Hu +1

Though voting-based consensus algorithms in Blockchain outperform proof-based ones in energy- and transaction-efficiency, they are prone to incur wrong elections and bribery electi…

cs.GT20191 cited

Hopping-Proof and Fee-Free Pooled Mining in Blockchain

Hongwei Shi, Shengling Wang, Qin Hu +3

The pool-hopping attack casts down the expected profits of both the mining pool and honest miners in Blockchain. The mainstream countermeasures, namely PPS (pay-per-share) and PPLN…