PrivaCIAS - Privacy as Contextual Integrity in Decentralized Multi-Agent Systems

Contextual Integrity has been proposed to define privacy in an unusual way. Most approaches take into account a sensitivity level or a privacy circle'': the information is said to be either private or public and to be constrained to a given group of agents, \textit{e.g.}my friends'', when private. In the opposite, Contextual Integrity states that any information transmitted can make this transmission a privacy violation depending on its context. In this thesis, we use this theory to develop a novel model that one can use in an open and decentralized virtual community to socially enforce privacy. This thesis defines the PrivaCIAS model, in which privacy constraints are formally described to be used to detect privacy violations according to the Contextual Integrity theory. The PrivaCIAS model provides norms to agents in order to make them implement social control. The model does not require a central authority, it gives control to the agents for detecting privacy violations (through Contextual Integrity) and excluding violating agents from the system through social exclusion. This model targets decentralized social networks as a main application domain.

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Source https://theses.hal.science/tel-00843082
Author Krupa, Yann
Maintainer CCSD
Last Updated May 10, 2026, 09:54 (UTC)
Created May 10, 2026, 09:54 (UTC)
Identifier NNT: 2012EMSE0657
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Département Informatique pour les Systèmes Coopératifs Ouverts et Décentralisés (ISCOD-ENSMSE) ; École des Mines de Saint-Étienne (Mines Saint-Étienne MSE) ; Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Henri Fayol
creator Krupa, Yann
date 2012-09-10T00:00:00
harvest_object_id 2efe84e7-f0d2-40f2-bece-c3221d770e4d
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-30T00:00:00
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