Trust Hardware Based Secured Privacy Preserving Computation System for Three-Dimensional Data
| Autor: | Jinlin Xu, Munan Yuan, Li Xiru, Xiaofeng Li, Haibo Tan |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
blockchain
Information privacy TK7800-8360 Computer Networks and Communications Computer science 0211 other engineering and technologies Data security 02 engineering and technology privacy Ethereum Distributed data store Node (computer science) Intel SGX 0202 electrical engineering electronic engineering information engineering Data Protection Act 1998 Isolation (database systems) Electrical and Electronic Engineering 021110 strategic defence & security studies business.industry trusted execution environment dual hybrid isolation transaction Hardware and Architecture Control and Systems Engineering Signal Processing Graph (abstract data type) 020201 artificial intelligence & image processing 3D data Electronics business Raw data Computer network |
| Zdroj: | Electronics, Vol 10, Iss 1546, p 1546 (2021) Electronics Volume 10 Issue 13 |
| ISSN: | 2079-9292 |
| DOI: | 10.3390/electronics10131546 |
| Popis: | Three-dimensional (3D) data are easily collected in an unconscious way and are sensitive to lead biological characteristics exposure. Privacy and ownership have become important disputed issues for the 3D data application field. In this paper, we design a privacy-preserving computation system (SPPCS) for sensitive data protection, based on distributed storage, trusted execution environment (TEE) and blockchain technology. The SPPCS separates a storage and analysis calculation from consensus to build a hierarchical computation architecture. Based on a similarity computation of graph structures, the SPPCS finds data requirement matching lists to avoid invalid transactions. With TEE technology, the SPPCS implements a dual hybrid isolation model to restrict access to raw data and obscure the connections among transaction parties. To validate confidential performance, we implement a prototype of SPPCS with Ethereum and Intel Software Guard Extensions (SGX). The evaluation results derived from test datasets show that (1) the enhanced security and increased time consumption (490 ms in this paper) of multiple SGX nodes need to be balanced (2) for a single SGX node to enhance data security and preserve privacy, an increased time consumption of about 260 ms is acceptable (3) the transaction relationship cannot be inferred from records on-chain. The proposed SPPCS implements data privacy and security protection with high performance. |
| Databáze: | OpenAIRE |
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