Vie privée

Résumé

vignette|droite|Dessin de Cham dans Le Charivari en 1868 : « Le portrait de ma femme que vous envoyez à l’Exposition ? Vous lui avez mis un grain de beauté sous le bras gauche, c’est de la vie privée. Je vous fais un procès ». La vie privée (du latin privatus, « séparé de, privé de ») est la capacité, pour une personne ou pour un groupe de personnes, de s'isoler afin de protéger son bien-être. Les limites de la vie privée ainsi que ce qui est considéré comme privé diffèrent selon les groupes, les cultures et les individus, selon les coutumes et les traditions bien qu'il existe toujours un certain tronc commun. La vie privée peut parfois s'apparenter à l'anonymat et à la volonté de rester hors de la vie publique. Quand quelque chose est dit « privé » pour une personne, cela signifie que généralement qu'à cette chose sont rattachés des sentiments spéciaux et personnels. Le degré de privatisation de l'information dépend donc de la façon dont le public pourrait la recevoir, ce qui diffèr

Source officielle

https://fr.wikipedia.org/wiki/Vie_priv%C3%A9e

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Many real-life optimization problems involve multiple entities, or agents (individuals, companies...), with their own private constraints and preferences, communicating with each other in order to find a solution that maximizes the overall public satisfaction. In Artificial Intelligence, the field of Distributed Constraint Optimization (DCOP) has been addressing such multi-agent optimization problems, through distributed message-passing algorithms such as the DPOP algorithm. However, the research in DCOP has been neglecting the privacy of the information exchanged by the agents during the computing of the solution, which is critical to many real-life problems. While agents are willing to cooperate with each other to produce an optimal solution, they are most often reluctant to reveal their private constraints and preferences to other, which hinders this cooperation. The goal of this project was to implement, test, and evaluate a secured version of DPOP, P-DPOP. P-DPOP provides strong agent privacy and topology privacy by randomization, constraints privacy and limited decision privacy by obfuscation. The algorithm was implemented in Java, as part of the open-source FRODO platform for DCOP.

2010

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Walking through Cerdà's Plan. (Re) Introducing Networked public Space into the Example's Courtyards

Mathieu Hefti

The strength of the Barcelona's Eixample comes from its urban plan, a visionary project designed by Ildefons Cerdà in 1859. The original project proposed blocks with a central open space built on two or three sides, allowing the introduction of variation through the urban fabric. However, to increase density the courtyards were privatized thereby reducing the public realm to the streets. The process was nevertheless reversed in 1986 by a new bylaw promoting the recuperation of the courtyards for public space. This project reasserts Cerdà's agenda for a diverse public realm forming a fluid network through streets and reclaimed courtyards and creating unique localities along promenades within a repetitive system. To solve the relation between users and programs, the different uses can coexist by a set of levels, taking up the existing fragmentation of buildings' terraces. Housing is extended by communal gardens, preserving privacy, while cafés and retail expand their activities on the interior and children and the elderly find social activities. The design of these itineraries is solved through parametric optimization, using a gaming pathfinder algorithm, with emphasis on the privacy condition of each block. The engine uses agents (virtual people) to determine the appropriate location and permeability of the threshold between street and courtyard. It is able to manage systematically small, human-scale interventions to (re) introduce a walking dimension into Cerdà's urban fabric.

2012

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Being able to exploit large and heterogeneous medical data is crucial for realizing the promise of precision medicine to its full potential. Yet, currently, due to the presence of multiple and fragmented systems at different clinical sites, it is often difficult to enable researchers to access the data they need. Privacy and security concerns also represent major obstacles that need to be overcome in order to provide access to sensitive medical data that are usually not exposed by clinical sites for the fear of data leaks. To address these challenges, we propose a system that employs Glowing Bear as a common front end to the widespread clinical research platforms i2b2, tranSMART and MedCo. Our proposed system uses IRCT, the official implementation of the PIC-SURE API, which acts as an interoperability layer that translates clinical research queries into native API languages. With our work, we take a step towards the technical convergence of i2b2 and tranSMART, giving clinical sites the means to share their data more easily. Even more, with the support of MedCo, a cohort explorer with strong privacy and security guarantees based on federated i2b2 instances, we enable clinical sites to share sensitive data that would be difficult to share otherwise.

2018

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