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Data trustworthiness in Internet of Things: A taxonomy and future directions

Haron, N. and Jaafar, J. and Aziz, I.A. and Hassan, M.H. and Shapiai, M.I. (2018) Data trustworthiness in Internet of Things: A taxonomy and future directions. 2017 IEEE Conference on Big Data and Analytics, ICBDA 2017, 2018-J . pp. 25-30.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Data Trustworthiness in Internet of Things (IoT) is a significant concern as the decision-making process, and actionable insights rely entirely on the data. False or misleading data could lead to wrong decisions with severe consequences. Data trustworthiness is the possibility to ascertain the correctness of the data provided by the data source. Current approaches for measuring data trustworthiness are generally meant for web and traditional sensor network. These methods are not applicable for IoT data since IoT has inherently different nature than other paradigms or domains. However, there are limited extant works on the data trustworthiness for IoT sensor data. Therefore, in this paper, we review the current developments in this area. A taxonomy of Data Trustworthiness for IoT Sensor Data is also presented according to the identified features from the extant works. Moreover, based on the observations, future directions are also proposed. © 2017 IEEE.

Item Type:Article
Impact Factor:cited By 0; Conference of 2017 IEEE Conference on Big Data and Analytics, ICBDA 2017 ; Conference Date: 16 November 2017 Through 17 November 2017; Conference Code:134594
Uncontrolled Keywords:Decision making; Internet of things; Sensor networks; Taxonomies; Trusted computing, data trustworthiness; Data-source; Decision making process; Internet of Things (IOT); IoT data; Measuring data; Sensor data, Big data
Departments / MOR / COE:Research Institutes > Institute for Autonomous Systems
ID Code:21777
Deposited By: Ahmad Suhairi
Deposited On:08 Aug 2018 02:01
Last Modified:10 Jan 2019 07:33

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