[en] We study coercion-resistance for online exams. We propose two new properties, Anonymous Submission and Single-Blindness which preserve the anonymity of the links between tests, test takers, and examiners even when the parties coerce one another into revealing secrets. The properties are relevant: not even Remark!, a secure exam protocol that satisfies anonymous marking and anonymous examiners, results to be coercion resistant. Then, we propose a coercion-resistance protocol which satisfies, in addition to known anonymity properties, the two novel properties we have introduced. We prove our claims formally in ProVerif. The paper has also another contribution: it describes an attack (and a fix) to an exponentiation mixnet that Remark! uses to ensure unlinkability. We use the secure version of the mixnet in our new protocol.
Disciplines :
Computer science
Author, co-author :
RAKEEI, Mohammadamin ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > IRiSC
GIUSTOLISI, Rosario ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Computer Science > Department of Computer Science ; Department of Computer Science, IT University of Copenhagen, Copenhagen, Denmark
LENZINI, Gabriele ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > IRiSC
External co-authors :
yes
Language :
English
Title :
Secure Internet Exams Despite Coercion
Publication date :
24 February 2023
Event name :
17th DPM International Workshop on Data Privacy Management
Event date :
26-09-2022 => 30-09-2022
Main work title :
Data Privacy Management, Cryptocurrencies and Blockchain Technology - ESORICS 2022 International Workshops, DPM 2022 and CBT 2022, Revised Selected Papers
Editor :
Garcia-Alfaro, Joaquin
Publisher :
Springer Science and Business Media Deutschland GmbH
Acknowledgement. Rakeei and Lenzini’s research is supported by the ANR and FNR international project INTER/AN/20/14926102 - “Secure and Veriflable Electronic Testing and Assessment Systems” (SEVERITAS). Giustolisi is supported by the Villum Foundation, within the project “Enabling User Accountable Mechanisms in Decision Systems”.
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