CAP-A: A Suite of Tools for Data Privacy Evaluation of Mobile Applications

Chrysakis, Ioannis; Flouris, Giorgos; Ioannidis, George; Makridaki, Maria; Patkos, Theodore; Roussakis, Yannis; Samaritakis, Georgios; Stan, Alexandru; Tsampanaki, Nikoleta; Tzortzakakis, Elias; Ymeralli, Elisjana

doi:10.3233/faia200881

Cited by 2 publications

(2 citation statements)

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“…About the CAP-A portal. The Rewarding Framework (RF) was implemented as a fundamental component of the CAP-A portal, a crowdsourcing platform aiming to raise privacy awareness in mobile applications [12,11]. In CAP-A portal we applied the proposed rewarding features and components of the RF to reward users' contribution in crowdsourcing privacy tasks.…”

Section: The Rewarding Framework (Rf)mentioning

confidence: 99%

A Rewarding Framework for Crowdsourcing to Increase Privacy Awareness

Chrysakis

Flouris

Makridaki

et al. 2021

Data and Applications Security and Privacy XXXV

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Digital applications typically describe their privacy policy in lengthy and vague documents (called PrPs), but these are rarely read by users, who remain unaware of privacy risks associated with the use of these digital applications. Thus, users need to become more aware of digital applications' policies and, thus, more confident about their choices. To raise privacy awareness, we implemented the CAP-A portal, a crowdsourcing platform which aggregates knowledge as extracted from PrP documents and motivates users in performing privacy-related tasks. The Rewarding Framework is one of the most critical components of the platform. It enhances user motivation and engagement by combining features from existing successful rewarding theories. In this work, we describe this Rewarding Framework, and show how it supports users to increase their privacy knowledge level by engaging them to perform privacy-related tasks, such as annotating PrP documents in a crowdsourcing environment. The proposed Rewarding Framework was validated by pilots ran in the frame of the European project CAP-A and by a user evaluation focused on its impact in terms of engagement and raising privacy awareness. The results show that the Rewarding Framework improves engagement and motivation, and increases users' privacy awareness.

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Section: The Rewarding Framework (Rf)mentioning

confidence: 99%

A Rewarding Framework for Crowdsourcing to Increase Privacy Awareness

Chrysakis

Flouris

Makridaki

et al. 2021

Data and Applications Security and Privacy XXXV

Self Cite

View full text Add to dashboard Cite

show abstract

“…https://cap-a.eu/, funded by NGI Trust, and implemented by the authors4 In the context of this paper, the term PrP refers to any type of Privacy Policy, Terms of Use, Consent Form etc document prescribing legally binding obligation on behalf of a developer concerning a particular app 5. Similar info, with screenshots, can be found in[14].I. Chrysakis et al / Evaluating the Data Privacy of Mobile Applications Through Crowdsourcing…”

mentioning

confidence: 99%

Evaluating the Data Privacy of Mobile Applications Through Crowdsourcing

Chrysakis

Flouris

Ioannidis³

et al. 2020

Frontiers in Artificial Intelligence and Applications

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Consumers are largely unaware regarding the use being made to the data that they generate through smart devices, or their GDPR-compliance, since such information is typically hidden behind vague privacy policy documents, which are often lengthy, difficult to read (containing legal terms and definitions) and frequently changing. This paper describes the activities of the CAP-A project, whose aim is to apply crowdsourcing techniques to evaluate the privacy friendliness of apps, and to allow users to better understand the content of Privacy Policy documents and, consequently, the privacy implications of using any given mobile app. To achieve this, we developed a set of tools that aim at assisting users to express their own privacy concerns and expectations and assess the mobile apps’ privacy properties through collective intelligence.

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CAP-A: A Suite of Tools for Data Privacy Evaluation of Mobile Applications

Cited by 2 publications

References 3 publications

A Rewarding Framework for Crowdsourcing to Increase Privacy Awareness

A Rewarding Framework for Crowdsourcing to Increase Privacy Awareness

Evaluating the Data Privacy of Mobile Applications Through Crowdsourcing

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