Literature DB >> 32079329

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

Yongkai Fan1,2,3, Guanqun Zhao3, Kuan-Ching Li4, Bin Zhang5, Gang Tan6, Xiaofeng Sun3, Fanglue Xia3.   

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.

Entities:  

Keywords:  IoT; IoT nodes; security; security framework

Year:  2020        PMID: 32079329     DOI: 10.3390/s20041090

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Classification of botnet attacks in IoT smart factory using honeypot combined with machine learning.

Authors:  Seungjin Lee; Azween Abdullah; Nz Jhanjhi; Sh Kok
Journal:  PeerJ Comput Sci       Date:  2021-01-25
  1 in total

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