Abstract
We present \(\mathcal {PCS}\), a privacy-preserving certification mechanism that allows users to conduct anonymous and unlinkable actions. The mechanism is built over an attribute-based signature construction. The proposal is proved secure against forgery and anonymity attacks. A use case on the integration of \(\mathcal {PCS}\) to enhance the privacy of learners of an e-assessment environment, and some details of the ongoing implementation, are briefly presented.
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- 1.
Source code snippets available at http://j.mp/PKIPCSgit.
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This work is supported by the H2020-ICT-2015/H2020-ICT-2015 TeSLA project An Adaptive Trust-based e-assessment System for Learning, Number 688520.
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Kaaniche, N., Laurent, M., Rocher, PO., Kiennert, C., Garcia-Alfaro, J. (2017). \(\mathcal {PCS}\), A Privacy-Preserving Certification Scheme. In: Garcia-Alfaro, J., Navarro-Arribas, G., Hartenstein, H., Herrera-Joancomartí, J. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2017 2017. Lecture Notes in Computer Science(), vol 10436. Springer, Cham. https://doi.org/10.1007/978-3-319-67816-0_14
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