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On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †

Data integrity is a prerequisite for ensuring data availability of IoT data and has received extensive attention in the field of IoT big data security. Stream computing systems are widely used in the field of IoT for real-time data acquisition and computing. However, the real-time, volatility, sudde...

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Autores principales: Wang, Hongyuan, Zu, Baokai, Zhu, Wanting, Li, Yafang, Wu, Jingbang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460000/
https://www.ncbi.nlm.nih.gov/pubmed/36080969
http://dx.doi.org/10.3390/s22176496
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author Wang, Hongyuan
Zu, Baokai
Zhu, Wanting
Li, Yafang
Wu, Jingbang
author_facet Wang, Hongyuan
Zu, Baokai
Zhu, Wanting
Li, Yafang
Wu, Jingbang
author_sort Wang, Hongyuan
collection PubMed
description Data integrity is a prerequisite for ensuring data availability of IoT data and has received extensive attention in the field of IoT big data security. Stream computing systems are widely used in the field of IoT for real-time data acquisition and computing. However, the real-time, volatility, suddenness, and disorder of stream data make data integrity verification difficult. According to the survey, there is no mature and universal solution. To solve this issue, we constructed a data integrity verification algorithm scheme of the stream computing system (S-DIV) by utilizing homomorphic message authentication code and pseudo-random function security assumption. Furthermore, based on S-DIV, an external data integrity tracking and verification system is constructed to track and analyze the message data stream in real time. By verifying the data integrity of message during the whole life cycle, the problem of data corruption or data loss can be found in time, and error alarm and message recovery can be actively implemented. Then, we conduct the formal security analysis under the standard model and, finally, implement the S-DIV scheme in simulation environment. Experimental results show that the scheme can guarantee data integrity in an acceptable time without affecting the efficiency of the original system.
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spelling pubmed-94600002022-09-10 On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT † Wang, Hongyuan Zu, Baokai Zhu, Wanting Li, Yafang Wu, Jingbang Sensors (Basel) Article Data integrity is a prerequisite for ensuring data availability of IoT data and has received extensive attention in the field of IoT big data security. Stream computing systems are widely used in the field of IoT for real-time data acquisition and computing. However, the real-time, volatility, suddenness, and disorder of stream data make data integrity verification difficult. According to the survey, there is no mature and universal solution. To solve this issue, we constructed a data integrity verification algorithm scheme of the stream computing system (S-DIV) by utilizing homomorphic message authentication code and pseudo-random function security assumption. Furthermore, based on S-DIV, an external data integrity tracking and verification system is constructed to track and analyze the message data stream in real time. By verifying the data integrity of message during the whole life cycle, the problem of data corruption or data loss can be found in time, and error alarm and message recovery can be actively implemented. Then, we conduct the formal security analysis under the standard model and, finally, implement the S-DIV scheme in simulation environment. Experimental results show that the scheme can guarantee data integrity in an acceptable time without affecting the efficiency of the original system. MDPI 2022-08-29 /pmc/articles/PMC9460000/ /pubmed/36080969 http://dx.doi.org/10.3390/s22176496 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Hongyuan
Zu, Baokai
Zhu, Wanting
Li, Yafang
Wu, Jingbang
On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title_full On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title_fullStr On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title_full_unstemmed On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title_short On the Design and Implementation of the External Data Integrity Tracking and Verification System for Stream Computing System in IoT †
title_sort on the design and implementation of the external data integrity tracking and verification system for stream computing system in iot †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460000/
https://www.ncbi.nlm.nih.gov/pubmed/36080969
http://dx.doi.org/10.3390/s22176496
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