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Chunkai Dai

dblp:250/5912 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0002-2963-941XORCID · reported

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

Security and privacy · 1

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 · 50% Hardware security and side channels · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Blockchain and cryptocurrency security
data trading
0.412020
SDTE: A Secure Blockchain-Based Data Trading Ecosystem · IEEE Trans. Inf. Forensics Secur. 2020
Hardware security and side channels
trusted execution environments
0.412020
SDTE: A Secure Blockchain-Based Data Trading Ecosystem · IEEE Trans. Inf. Forensics Secur. 2020

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

blockchain · 0.4Intel SGX · 0.4
YearPublicationVenuePosition
2020 SDTE: A Secure Blockchain-Based Data Trading Ecosystem
abstract
Data, a key asset in our data-driven economy, has fueled the emergence of a new data trading industry. However, there are a number of limitations in conventional data trading platforms due to the existence of dishonest buyer/data broker. To mitigate these limitations, we posit the importance of a data processing-as-a-service model, which complements the conventional data hosting/exchange-as-a-service model. Specifically, in this paper, we introduce a secure data trading ecosystem and present a new blockchain-based data trading ecosystem (hereafter referred to as SDTE). In the ecosystem, both data broker and buyer are not able to obtain access to the seller's raw data, as they are only getting access to the analysis findings that they require. In other words, we reduce the challenge of securing the dataset to the challenge to secure the data processing. We also build a security model to analyze the data trading market and describe a new set of trading protocols for the entire data trading market. To demonstrate utility, we implement our proposed secure data trading platform (SDTP) on Ethereum & Intel's Software Guard Extensions (SGX) and perform an in-depth analysis.
Weiqi Dai, Chunkai Dai, Kim-Kwang Raymond Choo, Changze Cui, Deqing Zou, Hai Jin 0001
IEEE Trans. Inf. Forensics Secur.2