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Abstract
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.
Keywords
data privacy, mobile apps, GDPR, crowdsourcing, collective intelligence

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Citation

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MLA
Chrysakis, Ioannis, et al. “Evaluating the Data Privacy of Mobile Applications through Crowdsourcing.” Legal Knowledge and Information Systems, edited by S. Villata et al., vol. 334, IOS, 2020, pp. 219–22, doi:10.3233/faia200868.
APA
Chrysakis, I., Flouris, G., Ioannidis, G., Makridaki, M., Patkos, T., Roussakis, Y., … Ymeralli, E. (2020). Evaluating the data privacy of mobile applications through crowdsourcing. In S. Villata, J. Harasta, & P. Kremen (Eds.), Legal knowledge and information systems (Vol. 334, pp. 219–222). https://doi.org/10.3233/faia200868
Chicago author-date
Chrysakis, Ioannis, Giorgos Flouris, George Ioannidis, Maria Makridaki, Theodore Patkos, Yannis Roussakis, Georgios Samaritakis, et al. 2020. “Evaluating the Data Privacy of Mobile Applications through Crowdsourcing.” In Legal Knowledge and Information Systems, edited by S. Villata, J. Harasta, and P. Kremen, 334:219–22. IOS. https://doi.org/10.3233/faia200868.
Chicago author-date (all authors)
Chrysakis, Ioannis, Giorgos Flouris, George Ioannidis, Maria Makridaki, Theodore Patkos, Yannis Roussakis, Georgios Samaritakis, Alexandru Stan, Nikoleta Tsampanaki, Elias Tzortzakakis, and Elisjana Ymeralli. 2020. “Evaluating the Data Privacy of Mobile Applications through Crowdsourcing.” In Legal Knowledge and Information Systems, ed by. S. Villata, J. Harasta, and P. Kremen, 334:219–222. IOS. doi:10.3233/faia200868.
Vancouver
1.
Chrysakis I, Flouris G, Ioannidis G, Makridaki M, Patkos T, Roussakis Y, et al. Evaluating the data privacy of mobile applications through crowdsourcing. In: Villata S, Harasta J, Kremen P, editors. Legal knowledge and information systems. IOS; 2020. p. 219–22.
IEEE
[1]
I. Chrysakis et al., “Evaluating the data privacy of mobile applications through crowdsourcing,” in Legal knowledge and information systems, virtual event, 2020, vol. 334, pp. 219–222.
@inproceedings{8685895,
  abstract     = {{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.}},
  author       = {{Chrysakis, Ioannis and Flouris, Giorgos and Ioannidis, George and Makridaki, Maria and Patkos, Theodore and Roussakis, Yannis and Samaritakis, Georgios and Stan, Alexandru and Tsampanaki, Nikoleta and Tzortzakakis, Elias and Ymeralli, Elisjana}},
  booktitle    = {{Legal knowledge and information systems}},
  editor       = {{Villata, S. and Harasta, J. and Kremen, P.}},
  isbn         = {{9781643681504}},
  issn         = {{0922-6389}},
  keywords     = {{data privacy,mobile apps,GDPR,crowdsourcing,collective intelligence}},
  language     = {{eng}},
  location     = {{virtual event}},
  pages        = {{219--222}},
  publisher    = {{IOS}},
  title        = {{Evaluating the data privacy of mobile applications through crowdsourcing}},
  url          = {{http://dx.doi.org/10.3233/faia200868}},
  volume       = {{334}},
  year         = {{2020}},
}

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