Cargando…

Privacy Engineering for Domestic IoT: Enabling Due Diligence

The EU’s General Data Protection Regulation (GDPR) has recently come into effect and insofar as Internet of Things (IoT) applications touch EU citizens or their data, developers are obliged to exercise due diligence and ensure they undertake Data Protection by Design and Default (DPbD). GDPR mandate...

Descripción completa

Detalles Bibliográficos
Autores principales: Lodge, Tom, Crabtree, Andy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832666/
https://www.ncbi.nlm.nih.gov/pubmed/31658736
http://dx.doi.org/10.3390/s19204380
_version_ 1783466226982322176
author Lodge, Tom
Crabtree, Andy
author_facet Lodge, Tom
Crabtree, Andy
author_sort Lodge, Tom
collection PubMed
description The EU’s General Data Protection Regulation (GDPR) has recently come into effect and insofar as Internet of Things (IoT) applications touch EU citizens or their data, developers are obliged to exercise due diligence and ensure they undertake Data Protection by Design and Default (DPbD). GDPR mandates the use of Data Protection Impact Assessments (DPIAs) as a key heuristic enabling DPbD. However, research has shown that developers generally lack the competence needed to deal effectively with legal aspects of privacy management and that the difficulties of complying with regulation are likely to grow considerably. Privacy engineering seeks to shift the focus from interpreting texts and guidelines or consulting legal experts to embedding data protection within the development process itself. There are, however, few examples in practice. We present a privacy-oriented, flow-based integrated development environment (IDE) for building domestic IoT applications. The IDE enables due diligence in (a) helping developers reason about personal data during the actual in vivo construction of IoT applications; (b) advising developers as to whether or not the design choices they are making occasion the need for a DPIA; and (c) attaching and making available to others (including data processors, data controllers, data protection officers, users and supervisory authorities) specific privacy-related information that has arisen during an application’s development.
format Online
Article
Text
id pubmed-6832666
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-68326662019-11-25 Privacy Engineering for Domestic IoT: Enabling Due Diligence Lodge, Tom Crabtree, Andy Sensors (Basel) Article The EU’s General Data Protection Regulation (GDPR) has recently come into effect and insofar as Internet of Things (IoT) applications touch EU citizens or their data, developers are obliged to exercise due diligence and ensure they undertake Data Protection by Design and Default (DPbD). GDPR mandates the use of Data Protection Impact Assessments (DPIAs) as a key heuristic enabling DPbD. However, research has shown that developers generally lack the competence needed to deal effectively with legal aspects of privacy management and that the difficulties of complying with regulation are likely to grow considerably. Privacy engineering seeks to shift the focus from interpreting texts and guidelines or consulting legal experts to embedding data protection within the development process itself. There are, however, few examples in practice. We present a privacy-oriented, flow-based integrated development environment (IDE) for building domestic IoT applications. The IDE enables due diligence in (a) helping developers reason about personal data during the actual in vivo construction of IoT applications; (b) advising developers as to whether or not the design choices they are making occasion the need for a DPIA; and (c) attaching and making available to others (including data processors, data controllers, data protection officers, users and supervisory authorities) specific privacy-related information that has arisen during an application’s development. MDPI 2019-10-10 /pmc/articles/PMC6832666/ /pubmed/31658736 http://dx.doi.org/10.3390/s19204380 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lodge, Tom
Crabtree, Andy
Privacy Engineering for Domestic IoT: Enabling Due Diligence
title Privacy Engineering for Domestic IoT: Enabling Due Diligence
title_full Privacy Engineering for Domestic IoT: Enabling Due Diligence
title_fullStr Privacy Engineering for Domestic IoT: Enabling Due Diligence
title_full_unstemmed Privacy Engineering for Domestic IoT: Enabling Due Diligence
title_short Privacy Engineering for Domestic IoT: Enabling Due Diligence
title_sort privacy engineering for domestic iot: enabling due diligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832666/
https://www.ncbi.nlm.nih.gov/pubmed/31658736
http://dx.doi.org/10.3390/s19204380
work_keys_str_mv AT lodgetom privacyengineeringfordomesticiotenablingduediligence
AT crabtreeandy privacyengineeringfordomesticiotenablingduediligence