A Privacy Engineering Framework for the Internet of Things

Kung, Antonio; Kargl, Frank; Suppan, Santiago; Cuéllar, Jorge; Pöhls, Henrich C.; Kapovits, Adam; McDonnell, Nicolás Notario; Martín, Yod Samuel

doi:10.1007/978-3-319-50796-5_7

Cited by 13 publications

(6 citation statements)

References 15 publications

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“…For specific works of privacy in IoT, privacy maintaining framework for IoT was developed by Kung [39]. In this work, the authors focused on data controllers, data processors, and integrators for privacy preservation.…”

Section: Privacy In Crowd-iotmentioning

confidence: 99%

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

2022

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Crowdsourcing can play an important role in the Internet of Things (IoT) applications for information sensing and gathering where the participants are equipped with geolocated devices. Mobile crowdsourcing can be seen as a new paradigm contributing to the development of the IoT. They can be merged to form a new and essential platform in crowdsourcing IoT paradigm for data collection from different sources and communication mediums. This paper presents a comprehensive survey for this new Crowdsourcing IoT paradigm from four different perspectives: (1) Architectures for Crowd-IoT; (2) Trustworthy, Privacy and Security for Crowd-IoT; (3) Resources, Sharing, Storage and Energy Considerations for Crowd-IoT; and (4) Applications for Crowd-IoT. This survey paper aims to increase awareness and encourage continuing developments and innovations from the research community and industry towards the Crowdsourcing IoT paradigm.

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Section: Privacy In Crowd-iotmentioning

confidence: 99%

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

2022

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“…Data Controller (DC) represents a natural or legal person, public authority, agency or other body which, alone or jointly with others, which determines the purposes and means of the processing of personal information [1,47,49,50].…”

Section: The Copri V2 Ontologymentioning

confidence: 99%

COPri v.2 — A core ontology for privacy requirements

Gharib

Giorgini

Mylopoulos

2021

Data & Knowledge Engineering

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“…Changing default privacy settings can limit unintended data disclosure [13,20]. Also blacken personal documents before sending them to third-party [51], called neutralize by [16], is a countermeasure.  Obfuscation "is the production of noise modeled on an existing signal" [52].…”

Section: Pre-disclosure Behaviorsmentioning

confidence: 99%

How to Protect My Privacy? - Classifying End-User Information Privacy Protection Behaviors

Ebbers

2020

Privacy and Identity Management. Data for Better Living: AI and Privacy

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The Internet and smart devices pose many risks at users' information privacy. Individuals are aware of that and try to counter tracking activities by applying different privacy protection behaviors. These are manifold and differ in scope, goal and degree of technology utilization. Although there is a lot of literature which investigates protection strategies, it is lacking holistic user-centric classifications. We review literature and identify 141 privacy protection behaviors end-users show. We map these results to 38 distinct categories and apply hybrid cart sorting to create a taxonomy, which we call the "End-User Information Privacy Protection Behavior Model" (EIPPBM).

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A Privacy Engineering Framework for the Internet of Things

Cited by 13 publications

References 15 publications

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and Applications

COPri v.2 — A core ontology for privacy requirements

How to Protect My Privacy? - Classifying End-User Information Privacy Protection Behaviors

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