Maass, Max ; Wichmann, Pascal ; Pridöhl, Henning ; Herrmann, Dominik (2021)
PrivacyScore: Improving Privacy and Security via Crowd-Sourced Benchmarks of Websites.
5th Annual Privacy Forum (APF 2017). Wien (07.-08.06.2017)
doi: 10.26083/tuprints-00017854
Conference or Workshop Item, Secondary publication, Postprint
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Item Type: | Conference or Workshop Item |
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Type of entry: | Secondary publication |
Title: | PrivacyScore: Improving Privacy and Security via Crowd-Sourced Benchmarks of Websites |
Language: | English |
Date: | 2021 |
Place of Publication: | Cham |
Year of primary publication: | 2017 |
Publisher: | Springer |
Book Title: | Privacy Technologies and Policy |
Series: | Lecture Notes in Computer Science |
Series Volume: | 10518 |
Event Title: | 5th Annual Privacy Forum (APF 2017) |
Event Location: | Wien |
Event Dates: | 07.-08.06.2017 |
DOI: | 10.26083/tuprints-00017854 |
Corresponding Links: | |
Origin: | Secondary publication service |
Abstract: | Website owners make conscious and unconscious decisions that affect their users, potentially exposing them to privacy and security risks in the process. In this paper we introduce PrivacyScore, an automated website scanning portal that allows anyone to benchmark security and privacy features of multiple websites. In contrast to existing projects, the checks implemented in PrivacyScore cover a wider range of potential privacy and security issues. Furthermore, users can control the ranking and analysis methodology. Therefore, PrivacyScore can also be used by data protection authorities to perform regularly scheduled compliance checks. In the long term we hope that the transparency resulting from the published assessments creates an incentive for website owners to improve their sites. The public availability of a first version of PrivacyScore was announced at the ENISA Annual Privacy Forum in June 2017. |
Status: | Postprint |
URN: | urn:nbn:de:tuda-tuprints-178548 |
Classification DDC: | 000 Generalities, computers, information > 004 Computer science |
Divisions: | 20 Department of Computer Science > Sichere Mobile Netze DFG-Graduiertenkollegs > Research Training Group 2050 Privacy and Trust for Mobile Users |
Date Deposited: | 07 Apr 2021 07:28 |
Last Modified: | 24 Nov 2022 14:44 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/17854 |
PPN: | 478852428 |
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