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Cankun Hou

dblp:379/6228 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0000-8662-8541ORCID · 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
Authentication and access control · 50% Privacy and data protection · 38% Hardware security and side channels · 12%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Authentication and access control › access control
fine-grained access control
0.812024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024
Privacy and data protection
privacy-preserving access control
0.812024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024
Authentication and access control › user authentication
credential verification
0.212024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024
Hardware security and side channels
trusted execution environments
0.212024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024
Distributed systems › fault tolerance › byzantine fault tolerance
asynchronous BFT
0.212024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024
Distributed systems › fault tolerance
byzantine fault tolerance
0.212024
FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System · IEEE Trans. Inf. Forensics Secur. 2024

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

trusted execution environment · 1.5asynchronous byzantine fault tolerance · 1.5
YearPublicationVenuePosition
2024 FACOS: Enabling Privacy Protection Through Fine-Grained Access Control With On-Chain and Off-Chain System
abstract
Data-driven landscape across finance, government, and healthcare, the continuous generation of information demands robust solutions for secure storage, efficient dissemination, and fine-grained access control. Blockchain technology emerges as a significant tool, offering decentralized storage while upholding the tenets of data security and accessibility. However, on-chain and off-chain strategies are still confronted with issues such as untrusted off-chain data storage, absence of data ownership, limited access control policy for clients, and a deficiency in data privacy and auditability. To solve these challenges, we propose a permissioned blockchain-based privacy-preserving fine-grained access control on-chain and off-chain system, namely FACOS. We applied three fine-grained access control solutions and comprehensively analyzed them in different aspects, which provides an intuitive perspective for system designers and clients to choose the appropriate access control method for their systems. Compared to similar work that only stores encrypted data in centralized or non-fault-tolerant IPFS systems, we enhanced off-chain data storage security and robustness by utilizing a highly efficient and secure asynchronous Byzantine fault tolerance (BFT) protocol in the off-chain environment. As each of the clients needs to be verified and authorized before accessing the data, we involved the Trusted Execution Environment (TEE)-based solution to verify the credentials of clients. Additionally, our evaluation results demonstrated that our system (https://github.com/cliu717/AsynchronousStorage) offers better scalability and practicality than other state-of-the-art designs. We deployed our system on Alibaba Cloud and Tencent Cloud and conducted multiple evaluations. The results indicate that it takes about 2.79 seconds for a client to execute the protocol for uploading and about 0.96 seconds for downloading. Compared to other decentralized systems, our system exhibits efficient latency for both download and upload operations.
Chao Liu 0039, Cankun Hou, Jianting Ning, Yusen Wu 0001
IEEE Trans. Inf. Forensics Secur.2