Article

Data Provenance Model for Internet of Things (IoT) Systems

Authors:

Habeeb Olufowobi,

Robert Engel,

Nathalie Baracaldo,

Luis Angel D. Bathen,

Samir Tata,

Heiko LudwigAuthors Info & Claims

Service-Oriented Computing – ICSOC 2016 Workshops: ASOCA, ISyCC, BSCI, and Satellite Events, Banff, AB, Canada, October 10–13, 2016, Revised Selected Papers

Pages 85 - 91

https://doi.org/10.1007/978-3-319-68136-8_8

Published: 10 October 2016 Publication History

Abstract

Internet of Things (IoT) systems and applications are increasingly deployed for critical use cases and therefore exhibit an increasing need for dependability. Data provenance deals with the recording, management and retrieval of information about the origin and history of data. We propose that the introduction of data provenance concepts into the IoT domain can help create dependable and trustworthy IoT systems by recording the lineage of data from basic sensor readings up to complex derived information created by software agents. In this paper, we present a data provenance model for IoT systems that is geared towards providing a generic mechanism for assuring the correctness and integrity of IoT applications and thereby reinforcing their trustworthiness and dependability for critical use cases.

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Cited By

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Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Sigwart MBorkowski MPeise MSchulte STai S(2019)Blockchain-based Data Provenance for the Internet of ThingsProceedings of the 9th International Conference on the Internet of Things10.1145/3365871.3365886(1-8)Online publication date: 22-Oct-2019
https://dl.acm.org/doi/10.1145/3365871.3365886

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Data Provenance Model for Internet of Things (IoT) Systems

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Published In

Service-Oriented Computing – ICSOC 2016 Workshops: ASOCA, ISyCC, BSCI, and Satellite Events, Banff, AB, Canada, October 10–13, 2016, Revised Selected Papers

Oct 2016

198 pages

ISBN:978-3-319-68135-1

DOI:10.1007/978-3-319-68136-8

Editors:
Khalil Drira
Université de Toulouse, Toulouse, France
,
Hongbing Wang
Southeast University, Jiangsu, China
,
Qi Yu
Rochester Institute of Technology, Rochester, New York, USA
,
Yan Wang
Macquarie University, Sydney, New South Wales, Australia
,
Yuhong Yan
Concordia University, Montreal, Québec, Canada
,
François Charoy
CNRS, Université de Lorraine, Nancy, France
,
Jan Mendling
Vienna University of Economics and Business, Vienna, Austria
,
Mohamed Mohamed
IBM Research, San Jose, California, USA
,
Zhongjie Wang
Harbin Institute of Technology, Harbin, China
,
Sami Bhiri
University of Monastir, Monastir, Tunisia

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Springer-Verlag

Berlin, Heidelberg

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Published: 10 October 2016

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Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Sigwart MBorkowski MPeise MSchulte STai S(2019)Blockchain-based Data Provenance for the Internet of ThingsProceedings of the 9th International Conference on the Internet of Things10.1145/3365871.3365886(1-8)Online publication date: 22-Oct-2019
https://dl.acm.org/doi/10.1145/3365871.3365886

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Securing Data Provenance in Internet of Things (IoT) Systems

Internet of Things (IoT): From awareness to continued use

Systematic Literature Review on Data Provenance in Internet of Things

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