A synthesis of industry-reported LLM risks and defensive deployments, capped with a conceptual 'LLM Design & Assurance' stack for trust and compliance.
Secure Internet Exams Despite Coercion
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We study coercion-resistance for online exams. We propose two properties, Anonymous Submission and Single-Blindness which, if hold, 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 satisfied 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.
citation-role summary
citation-polarity summary
fields
cs.CR 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Risks & Benefits of LLMs & GenAI for Platform Integrity, Healthcare Diagnostics, Financial Trust and Compliance, Cybersecurity, Privacy & AI Safety: A Comprehensive Survey, Roadmap & Implementation Blueprint
A synthesis of industry-reported LLM risks and defensive deployments, capped with a conceptual 'LLM Design & Assurance' stack for trust and compliance.