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arXiv 2407.03466cs.CR
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物联网数据溯源的安全方法:一项系统性文献综述

Security Approaches for Data Provenance in the Internet of Things: A Systematic Literature Review

Omair Faraj, David Megias, Joaquin Garcia-Alfaro

AI总结:

本文针对物联网资源受限设备的安全漏洞,通过系统性文献综述梳理物联网数据溯源的现有技术、实现方案、安全需求与性能指标,提出分类体系,指明开放问题与未来研究方向。

摘要:

物联网(IoT)依赖部署在无防护环境中的资源受限设备。受限于自身的资源约束特性,物联网系统易遭受安全攻击。数据溯源用于追踪数据的来源与流向,为保障物联网系统中的数据安全(包括可信度、机密性、完整性和可用性)提供了潜在解决方案。在单跳和多跳场景的数据传输过程中,系统可能面临不同类型的风险,尤其是物联网系统的互联互通特性会引发安全与隐私问题。攻击者可注入恶意数据或悄无声息地篡改数据,破坏数据的完整性与可信度。数据溯源通过记录数据的来源、历史流转过程和处理操作,为应对这些安全漏洞提供了途径。本文对物联网领域的数据溯源研究开展了系统性文献综述,梳理了现有技术、实际实现方案、安全需求与性能指标,对比了各类研究的贡献与不足,提出了物联网数据溯源发展的分类体系,明确了待解决的开放问题并给出了未来研究方向,为物联网场景下数据溯源研究的演进提供了有益参考。

英文摘要:

The Internet of Things (IoT) relies on resource-constrained devices deployed in unprotected environments. Given their constrained nature, IoT systems are vulnerable to security attacks. Data provenance, which tracks the origin and flow of data, provides a potential solution to guarantee data security, including trustworthiness, confidentiality, integrity, and availability in IoT systems. Different types of risks may be faced during data transmission in single-hop and multi-hop scenarios, particularly due to the interconnectivity of IoT systems, which introduces security and privacy concerns. Attackers can inject malicious data or manipulate data without notice, compromising data integrity and trustworthiness. Data provenance offers a way to record the origin, history, and handling of data to address these vulnerabilities. A systematic literature review of data provenance in IoT is presented, exploring existing techniques, practical implementations, security requirements, and performance metrics. Respective contributions and shortcomings are compared. A taxonomy related to the development of data provenance in IoT is proposed. Open issues are identified, and future research directions are presented, providing useful insights for the evolution of data provenance research in the context of the IoT.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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