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SNPL:物联网感知层中一种节点安全保障方案。

SNPL: One Scheme of Securing Nodes in IoT Perception Layer.

作者信息

Fan Yongkai, Zhao Guanqun, Li Kuan-Ching, Zhang Bin, Tan Gang, Sun Xiaofeng, Xia Fanglue

机构信息

Institute of Computer Science and Cybersecurity, Communication University of China, Beijing 100024, China.

Tus College of Digit, Beijing 100084, China.

出版信息

Sensors (Basel). 2020 Feb 17;20(4):1090. doi: 10.3390/s20041090.

Abstract

The trustworthiness of data is vital data analysis in the age of big data. In cyber-physical systems, most data is collected by sensors. With the increase of sensors as Internet of Things (IoT) nodes in the network, the security risk of data tampering, unauthorized access, false identify, and others are overgrowing because of vulnerable nodes, which leads to the great economic and social loss. This paper proposes a security scheme, Securing Nodes in IoT Perception Layer (SNPL), for protecting nodes in the perception layer. The SNPL is constructed by novel lightweight algorithms to ensure security and satisfy performance requirements, as well as safety technologies to provide security isolation for sensitive operations. A series of experiments with different types and numbers of nodes are presented. Experimental results and performance analysis show that SNPL is efficient and effective at protecting IoT from faulty or malicious nodes. Some potential practical application scenarios are also discussed to motivate the implementation of the proposed scheme in the real world.

摘要

在大数据时代,数据的可信度对于数据分析至关重要。在信息物理系统中,大多数数据是由传感器收集的。随着作为物联网(IoT)节点的传感器在网络中的增加,由于节点易受攻击,数据篡改、未经授权访问、身份伪造等安全风险不断增加,这会导致巨大的经济和社会损失。本文提出了一种用于保护感知层节点的安全方案,即物联网感知层节点安全保护(SNPL)。SNPL由新颖的轻量级算法构建而成,以确保安全性并满足性能要求,同时还采用了安全技术为敏感操作提供安全隔离。文中给出了一系列针对不同类型和数量节点的实验。实验结果和性能分析表明,SNPL在保护物联网免受故障或恶意节点影响方面是高效且有效的。还讨论了一些潜在的实际应用场景,以推动所提方案在现实世界中的实施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/205a/7070629/8306d3df3709/sensors-20-01090-g001.jpg

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