Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Pengchao Chen

dblp:237/5364 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-3201-4568ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Blockchain and cryptocurrency security · 46% Cryptographic primitives and cryptanalysis · 46% Cryptographic protocols and secure computation · 7%
Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic primitives and cryptanalysis › searchable encryption › public key encryption with keyword search
attribute-based keyword search
0.812024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Blockchain and cryptocurrency security
data trading
0.812024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Cryptographic primitives and cryptanalysis
searchable encryption
0.812024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Blockchain and cryptocurrency security
smart contract
0.812024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Cryptographic protocols and secure computation › proof systems
zero-knowledge proofs
0.212024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Algorithmic game theory and mechanism design › stackelberg game
pricing strategy
0.212024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024
Algorithmic game theory and mechanism design
stackelberg game
0.212024
SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain · IEEE Trans. Inf. Forensics Secur. 2024

Methods — techniques the papers use, named apart from their topics

zero-knowledge proofs · 1.5stackelberg game · 1.5attribute-based searchable encryption · 1.5
YearPublicationVenuePosition
2024 SFOM-DT: A Secure and Fair One-to-Many Data Trading Scheme Based on Blockchain
abstract
The requirements for large amounts of data have promoted the rapid emergence of an industry for trading data. However, the current one-to-one trading constraints in the existing data trading schemes lead to low security and low efficiency. To tackle the challenges, a novel one-to-many distributed data trading scheme is proposed based on blockchain, which enables a data seller to sell one piece of data to multiple data buyers simultaneously, saving storage resources and computing resources significantly. Firstly, some new smart contracts are devised for two decentralized applications. Then, attribute-based searchable encryption technology is proposed to establish a data circulation scheme that realizes end-to-end encryption of data and ensures data security and highly efficient access. Finally, an inspection mechanism based on zero-knowledge proof and a pricing strategy based on the Stackelberg game are designed to guarantee fairness in trading and maximize revenue. The experiment results show that, in comparison to one-to-one trading, the high efficiency of this data trading scheme gradually emerges as the number of buyers (n) is greater than 2, and the run time is less than 1/10 of the former when n =35. Furthermore, the pricing strategy can enable buyers and sellers to obtain more revenue when$\text {n} \gt 4$.
Shuming Xiong, Pengchao Chen, Shusheng Ge, Qiang Ni
IEEE Trans. Inf. Forensics Secur.2