relation: https://khub.utp.edu.my/scholars/8530/
title: Data trustworthiness in Internet of Things: A taxonomy and future directions
creator: Haron, N.
creator: Jaafar, J.
creator: Aziz, I.A.
creator: Hassan, M.H.
creator: Shapiai, M.I.
description: 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.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2017
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Haron, N. and Jaafar, J. and Aziz, I.A. and Hassan, M.H. and Shapiai, M.I.  (2017) Data trustworthiness in Internet of Things: A taxonomy and future directions.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047436649&doi=10.1109%2fICBDAA.2017.8284102&partnerID=40&md5=8f45dc3627632aa78af9ea3df0222e47
relation: 10.1109/ICBDAA.2017.8284102
identifier: 10.1109/ICBDAA.2017.8284102