TEDA:基于可信执行环境和区块链的物联网数据保护架构

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS
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引用次数: 0

摘要

摘要 随着物联网(IoT)的普及,每秒钟都会产生大量数据。通过分析这些数据,攻击者可以发起各种攻击以谋取利益,如数据篡改、恶意数据注入、身份欺骗等。为了解决这些问题,本文提出了基于可信执行环境和区块链的数据保护架构(TEDA)。在 TEDA 中,不同物联网的边缘设备维护一个联盟区块链,与云端一起实现数据的安全读写操作和验证。此外,为了确保边缘设备本地数据处理的安全,并管理内部轻量级设备,设计了基于英特尔 SGX 的模块。此外,还引入了一种新的事务结构来保护用户的访问模式。实验结果表明,与不带SGX的TEDA相比,带SGX的TEDA写入和读取的空间占用率分别为0.84(次)和1.07(次);与不带SGX的TEDA相比,带SGX的TEDA写入和读取的时间占用率分别为0.94(次)和0.90(次),这表明TEDA具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TEDA: a trusted execution environment-and-blockchain-based data protection architecture for Internet of Things

Abstract

With the popularity of the Internet of Things (IoT), massive amounts of data are generated every second. By analyzing this data, attackers can launch kinds of attacks for their own profits, such as data tampering, malicious data injection, identity deception etc. To solve these problems, in this paper, we propose a Trusted Execution Environment-and-Blockchain-based data protection architecture (TEDA). In TEDA, edge devices in different IoTs maintain a consortium blockchain to achieve the secure read/write operations and verification of data together with cloud. Besides, to secure the local data processing in edge devices and manage internal light-weight devices, an Intel SGX-based module is designed. Furthermore, a new transaction structure is introduced to protect user’s access pattern. The experimental results show that the space occupancy rates of write and read of TEDA with SGX are 0.84 \(\times \) and 1.07 \(\times \) than that of TEDA without SGX, and the time occupancy rates of write and read of TEDA with SGX are 0.94 \(\times \) and 0.90 \(\times \) than that of TEDA without SGX, which indicate TEDA has a good performance.

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来源期刊
Computing
Computing 工程技术-计算机:理论方法
CiteScore
8.20
自引率
2.70%
发文量
107
审稿时长
3 months
期刊介绍: Computing publishes original papers, short communications and surveys on all fields of computing. The contributions should be written in English and may be of theoretical or applied nature, the essential criteria are computational relevance and systematic foundation of results.
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