User privacy risk analysis for the Internet of Things

Aggarwal, Akash, Asif, Waqar ORCID: https://orcid.org/0000-0001-6774-3050, Azam, Habibul, Markovic, Milan, Rajarajan, Muttukrishnan and Edwards, Peter (2019) User privacy risk analysis for the Internet of Things. In: 6th IEEE International Conference on Internet of Things: Systems, Management and Security, 22-25 Oct, Spain.

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Abstract

The Internet of Things (IoT) refers to a large network of devices such as sensors and actuators in which diverse types of data is generated and shared. Data can be shared in its raw form or as a result of data processing activities performed by an IoT device (e.g. anonymization, aggregation, etc.). However, sharing such data introduces a multitude of risks which are influenced by data type, data harvesting granularity, user demographics and the device under consideration. In this work, we propose a novel extension to our attack tree risk model [1] to consider user preferences for sharing personal data. We enrich our earlier work by exploring more attacks and complimenting them with a user privacy-risk model. We evaluate this proposed model and identify a range of scenarios which can result in personal information privacy violation and thus provide a model for estimating the potential risk of an IoT ecosystem.

Item Type: Conference or Workshop Item (Paper)
ISBN: 9781728129495
Identifier: 10.1109/IOTSMS48152.2019.8939265
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Data privacy, Privacy, Smart meters, Internet of Things, Security, Data models, Manipulators
Subjects: Computing > Information security
Related URLs:
Depositing User: Waqar Asif
Date Deposited: 05 Dec 2020 00:52
Last Modified: 28 Aug 2021 07:14
URI: http://repository.uwl.ac.uk/id/eprint/7511

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