In-network generalized trustworthy data collection for event detection in cyber-physical systems

Sensors in Cyber-Physical Systems (CPS) are typically used to collect various aspects of the region of interest and transmit the data towards upstream nodes for further processing. However, data collection in CPS is often unreliable due to severe resource constraints (e.g., bandwidth and energy), en...

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Main Authors: Hafiz Ur Rahman, Guojun Wang, Md Zakirul Alam Bhuiyan, Jianer Chen
Format: Article
Language:English
Published: PeerJ Inc. 2021-05-01
Series:PeerJ Computer Science
Subjects:
Online Access:https://peerj.com/articles/cs-504.pdf
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author Hafiz Ur Rahman
Guojun Wang
Md Zakirul Alam Bhuiyan
Jianer Chen
author_facet Hafiz Ur Rahman
Guojun Wang
Md Zakirul Alam Bhuiyan
Jianer Chen
author_sort Hafiz Ur Rahman
collection DOAJ
description Sensors in Cyber-Physical Systems (CPS) are typically used to collect various aspects of the region of interest and transmit the data towards upstream nodes for further processing. However, data collection in CPS is often unreliable due to severe resource constraints (e.g., bandwidth and energy), environmental impacts (e.g., equipment faults and noises), and security concerns. Besides, detecting an event through the aggregation in CPS can be intricate and untrustworthy if the sensor's data is not validated during data acquisition, before transmission, and before aggregation. This paper introduces In-network Generalized Trustworthy Data Collection (IGTDC) framework for event detection in CPS. This framework facilitates reliable data for aggregation at the edge of CPS. The main idea of IGTDC is to enable a sensor's module to examine locally whether the event's acquired data is trustworthy before transmitting towards the upstream nodes. It further validates whether the received data can be trusted or not before data aggregation at the sink node. Additionally, IGTDC helps to identify faulty sensors. For reliable event detection, we use collaborative IoT tactics, gate-level modeling with Verilog User Defined Primitive (UDP), and Programmable Logic Device (PLD) to ensure that the event's acquired data is reliable before transmitting towards the upstream nodes. We employ Gray code in gate-level modeling. It helps to ensure that the received data is reliable. Gray code also helps to distinguish a faulty sensor. Through simulation and extensive performance analysis, we demonstrate that the collected data in the IGTDC framework is reliable and can be used in the majority of CPS applications.
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spelling doaj.art-fcfcd84e7bb24a2eb533f37476d0b3582022-12-21T22:48:21ZengPeerJ Inc.PeerJ Computer Science2376-59922021-05-017e50410.7717/peerj-cs.504In-network generalized trustworthy data collection for event detection in cyber-physical systemsHafiz Ur Rahman0Guojun Wang1Md Zakirul Alam Bhuiyan2Jianer Chen3School of Computer Science, Guangzhou University, Guangzhou, Guangdong Province, ChinaSchool of Computer Science, Guangzhou University, Guangzhou, Guangdong Province, ChinaDepartment of Computer and Information Sciences, Fordham University, New York, NY, United StatesSchool of Computer Science, Guangzhou University, Guangzhou, Guangdong Province, ChinaSensors in Cyber-Physical Systems (CPS) are typically used to collect various aspects of the region of interest and transmit the data towards upstream nodes for further processing. However, data collection in CPS is often unreliable due to severe resource constraints (e.g., bandwidth and energy), environmental impacts (e.g., equipment faults and noises), and security concerns. Besides, detecting an event through the aggregation in CPS can be intricate and untrustworthy if the sensor's data is not validated during data acquisition, before transmission, and before aggregation. This paper introduces In-network Generalized Trustworthy Data Collection (IGTDC) framework for event detection in CPS. This framework facilitates reliable data for aggregation at the edge of CPS. The main idea of IGTDC is to enable a sensor's module to examine locally whether the event's acquired data is trustworthy before transmitting towards the upstream nodes. It further validates whether the received data can be trusted or not before data aggregation at the sink node. Additionally, IGTDC helps to identify faulty sensors. For reliable event detection, we use collaborative IoT tactics, gate-level modeling with Verilog User Defined Primitive (UDP), and Programmable Logic Device (PLD) to ensure that the event's acquired data is reliable before transmitting towards the upstream nodes. We employ Gray code in gate-level modeling. It helps to ensure that the received data is reliable. Gray code also helps to distinguish a faulty sensor. Through simulation and extensive performance analysis, we demonstrate that the collected data in the IGTDC framework is reliable and can be used in the majority of CPS applications.https://peerj.com/articles/cs-504.pdfCyber-physical systemData qualityEvent monitoringData trustworthinessData dependabilitySecurity and privacy
spellingShingle Hafiz Ur Rahman
Guojun Wang
Md Zakirul Alam Bhuiyan
Jianer Chen
In-network generalized trustworthy data collection for event detection in cyber-physical systems
PeerJ Computer Science
Cyber-physical system
Data quality
Event monitoring
Data trustworthiness
Data dependability
Security and privacy
title In-network generalized trustworthy data collection for event detection in cyber-physical systems
title_full In-network generalized trustworthy data collection for event detection in cyber-physical systems
title_fullStr In-network generalized trustworthy data collection for event detection in cyber-physical systems
title_full_unstemmed In-network generalized trustworthy data collection for event detection in cyber-physical systems
title_short In-network generalized trustworthy data collection for event detection in cyber-physical systems
title_sort in network generalized trustworthy data collection for event detection in cyber physical systems
topic Cyber-physical system
Data quality
Event monitoring
Data trustworthiness
Data dependability
Security and privacy
url https://peerj.com/articles/cs-504.pdf
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AT guojunwang innetworkgeneralizedtrustworthydatacollectionforeventdetectionincyberphysicalsystems
AT mdzakirulalambhuiyan innetworkgeneralizedtrustworthydatacollectionforeventdetectionincyberphysicalsystems
AT jianerchen innetworkgeneralizedtrustworthydatacollectionforeventdetectionincyberphysicalsystems