Visible to the public Trustworthy Data Acquisition and Faulty Sensor Detection using Gray Code in Cyber-Physical System

TitleTrustworthy Data Acquisition and Faulty Sensor Detection using Gray Code in Cyber-Physical System
Publication TypeConference Paper
Year of Publication2020
Authorsur Rahman, Hafiz, Duan, Guihua, Wang, Guojun, Bhuiyan, Md Zakirul Alam, Chen, Jianer
Conference Name2020 IEEE 23rd International Conference on Computational Science and Engineering (CSE)
Date PublishedJan. 2021
PublisherIEEE
ISBN Number978-1-6654-0398-6
Keywordscomposability, cyber physical systems, data acquisition, Data models, event detection, False Data Detection, faulty sensor detection, Human Behavior, human factors, Internet of Things, pubcrawl, reliability, reliable data, resilience, Resiliency, Scientific computing, Sensor systems, Sensors, Trustworthy Systems, Wireless communication
AbstractDue to environmental influence and technology limitation, a wireless sensor/sensors module can neither store or process all raw data locally nor reliably forward it to a destination in heterogeneous IoT environment. As a result, the data collected by the IoT's sensors are inherently noisy, unreliable, and may trigger many false alarms. These false or misleading data can lead to wrong decisions once the data reaches end entities. Therefore, it is highly recommended and desirable to acquire trustworthy data before data transmission, aggregation, and data storing at the end entities/cloud. In this paper, we propose an In-network Generalized Trustworthy Data Collection (IGTDC) framework for trustworthy data acquisition and faulty sensor detection in the IoT environment. The key idea of IGTDC is to allow a sensor's module to examine locally whether the raw data is trustworthy before transmitting towards upstream nodes. It further distinguishes whether the acquired data can be trusted or not before data aggregation at the sink/edge node. Besides, IGTDC helps to recognize a faulty or compromised sensor. For a reliable data collection, we use collaborative IoT technique, gate-level modeling, and programmable logic device (PLD) to ensure that the acquired data is reliable before transmitting towards upstream nodes/cloud. We use a hardware-based technique called “Gray Code” to detect a faulty sensor. Through simulations we reveal that the acquired data in IGTDC framework is reliable that can make a trustworthy data collection for event detection, and assist to distinguish a faulty sensor.
URLhttps://ieeexplore.ieee.org/document/9345833
DOI10.1109/CSE50738.2020.00016
Citation Keyur_rahman_trustworthy_2020