Ping Lu 0008

dblp:39/7035-8 · DBLP profile ↗
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3ranked-venue papers in the field
0as first author
3since 2021 · last 2024
—ORCID · conflict

Domains — venue-derived; a paper can count in several

Big Data, Cloud & Distributed Data Systems · 3
YearPublicationVenuePosition
2024 SVP: Enhancing Security and Scalability for Metaverse Blockchain Through Integrating Stake in Voting-based Consensus Protocol
abstract
Blockchain has now become a critical infrastructure in Metaverse for storing and managing the digital resources of users, bridging the real and virtual worlds. However, consensus protocols in blockchains constrain the performance of their applications. While existing voting-based consensus protocols such as HotStuff and other Byzantine Fault Tolerance (BFT) protocols have optimized efficiency and scalability, they simply adopt a one-person-one-vote rule that is not aligned with the human-centric values of most blockchain applications, including Metaverse. Therefore, we propose Stake Voting Protocol (SVP), a secure and scalable consensus protocol, whose design philosophy is to consider validators’ stakes in the BFT protocol and introduce flexibility through a sliding window. We also propose a certification rule within the pipelined two-chain consensus process to enhance security. Furthermore, our epoch change and incentive mechanisms ensure dynamics and liveness, respectively. Finally, our analytical and experimental results demonstrate that the proposed SVP satisfies correctness and can resist specific attacks with low latency and high throughput.
Wuyang Li, Hui Li 0022, Qiufan Wu, Han Wang 0022, Weimin Zeng, Yanping Zhang 0008, Ping Lu 0008, Runhuai Huang
IEEE Big Data8
2022 Optimizing Parallel Proof of Vote Consensus Based on Mimic Security in Consortium Blockchains
abstract
Some Byzantine fault tolerant (BFT) consensus algorithm in consortium blockchains have lots of message broadcast to encroach bandwidth, which greatly affect the efficiency of consensus execution. Although reducing the number of global consensus nodes can help, it is also at the cost of reduced security. Based on the idea of Mimic Defense, this paper proposes a consensus framework for BFT consensus and takes the Parallel Proof of Vote (PPoV) algorithm as an example to design a randomized node sharding and role partitioning scheme to improve security of the consensus process without affecting efficiency much. In addition, the multimode adjudication group composed of the shard leaders can replace the single leader to complete voting statistics to improve the reliability of consensus results. Through theoretical analysis, it is known that the BFT consensus framework based on mimic security, taking PPoV as an example, has a strong defense effect against eclipse attacks and selfish mining. A simulation experiment is also designed to prove that through efficient iteration and dynamic threshold design, the adjudication group greatly improves the reliability of the results and the robustness of the algorithm.
Zhenwei Xiao, Hui Li 0022, Han Wang 0022, Qiongwei Ye, Shusheng Zou, Ping Lu 0008, Qi Lyu
IEEE Big Data7
2021 A Data Lightweight Scheme for Parallel Proof of Vote Consensus
abstract
Each blockchain’s node needs to store a backup of all blocks, resulting in the whole network needs O(n) storage space, which greatly affects the nodes’ scalability. Parallel proof of vote(PPoV) is a permissioned blockchain algorithm that uses block groups as the basic data structures. This paper proposes a data lightweight scheme for PPoV. In the bock group generation stage, the BLS algorithm is used to realize signature aggregation, and the storage space of block signature and vote signature is reduced from O(n) to O(1) without affecting the performance. In the storage stage, we use erasure code to implement storage partition for block groups and ensure the real-time recoverability of complete data. To speed up reading, the timeline-based model applies different storage strategies for hot and cold data. The experimental results show that the empty block group generated by BLS aggregation signature is smaller and less sensitive to the number of nodes. And the reduction ratio of storage space under a large number of transactions can be similar to the number of normal nodes.
Zixian Wang, Hui Li 0022, Han Wang 0022, Zhenwei Xiao, Ping Lu 0008, Zhenyuan Yang, Minglong Zhang, Peter Han Joo Chong
IEEE BigData5