Postdoc - Développement de Pets sur Mobile H/F - INRIA

A propos d'Inria

Inria, l'institut national de recherche dans les sciences et technologies du numérique, est en appui de l'État pour les stratégies nationales de recherche et d'innovation du numérique en tant qu'Agence de programmes. Inria mène plus de 300 projets de recherche et d'innovation avec ses 3500 scientifiques, ingénieurs et personnels d'appui, en partenariat avec les universités et l'écosystème numérique (entreprises, entrepreneurs, acteurs publics). Ensemble, nous explorons des domaines clés comme l'intelligence artificielle, la cybersécurité, l'informatique quantique, le Cloud, la transformation numérique de la santé, les jumeaux numériques ou encore les technologies numériques pour la défense. Nous construisons des solutions concrètes telles que des logiciels, des startups technologiques, des partenariats avec les entreprises du tissu national et des formations de pointe. Notre objectif : l'impact scientifique, technologique et industriel au service de la souveraineté numérique de la France.

Postdoc - développement de PETS sur mobile

Contrat renouvelable : Oui

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Ingénieur scientifique contractuel

A propos du centre ou de la direction fonctionnelle

Le centre de recherche Inria de l'Université Grenoble Alpes regroupe un peu moins de 600 personnes réparties au sein de 27 équipes de recherche et 8 services support à la recherche.

Son effectif est distribué sur 3 campus à Grenoble, en lien étroit avec les laboratoires et les établissements de recherche et d'enseignement supérieur (Université Grenoble Alpes, CNRS, CEA, INRAE, ...), mais aussi avec les acteurs économiques du territoire.

Présent dans les domaines du calcul et grands systèmes distribués, logiciels sûrs et systèmes embarqués, la modélisation de l'environnement à différentes échelles et la science des données et intelligence artificielle, Inria Grenoble - Rhône-Alpes participe au meilleur niveau à la vie scientifique internationale par les résultats obtenus et les collaborations tant en Europe que dans le reste du monde.

Contexte et atouts du poste

The collection of personal data and the associated privacy
issues are a subject firmly grounded in public debates. The
growing awareness of the population on privacy issues led to
stronger regulations on data protection (e.g., GDPR, HIPAA)
and contributed to the appearance of new services making
privacy an incentive vector such as privacy-based search
engine (e.g., Duckduckgo, Qwant), web browsing (e.g., Web
Proxy, Tor, Brave), or mailing (e.g., Protonmail).

However, the ever-increasing digitalization of our society
exposes individuals to omnipresent data collection. This mas-
sive collection of information exposes individuals to new
risks ranging from the disclosure of sensitive information
to increased manipulation through personal cognitive biases
facilitated by the exposure of our personality. The emergence
and development of AI have only amplified these risks despite
the regulatory effort at different levels (e.g., AI Act) which
highlights fundamental freedoms.

Once collected, personal information of various natures
(e.g., location, web search, web tracking, voice, pictures,
motion data, ...) can reveal many sensitive information. For
instance, recent works have demonstrated that mobility is
a very rich contextual information in the sense that it has
a strong inferential potential in terms of information that
can be predicted about the individuals whose movements
are recorded. Among other, researchers have shown that
analyzing mobility traces can reveal personal data about
individuals such as their points of interests (e.g., home and
place of work) [1], their race and gender [2], their social
network [3] as well as to predict their mobility [4], to
link accounts of the same user across different datasets [5]
and to uniquely identify users from anonymous datasets
or to conduct a de-anonymization attack [6]. Moreover,
it is possible to analyze the semantics of these mobility
traces to infer even more sensitive information such as their
religion [7]. In addition, other studies have also demonstrated
that the location is used for price discrimination [8].

Effectively protecting personal data is challenging. A large
number of protection mechanisms have been proposed in
the academic literature but very few have been adopted by
application providers and companies in the field and even
fewer by users. Furthermore, protecting data inherently also
comes with a loss of service and utility (i.e., there is no free
food) Data anonymization is rarely perfect, we are talking
more about the probability of risk depending on the means
used by an adversary to carry out a re-identification attack
(e.g., collection of auxiliary information, etc.). The risk is
necessarily greater for atypical people than for people more
similar to the rest of the population.

However, before asking the question of how to effectively
protect our location data and what risk remains, perhaps it is
better to ask whether it is relevant to generate this data and
let third parties collect it. Indeed, without collected personnal
data, the risk of disclosing information in an uncontrolled
manner does not exist. Raising user awareness by better
explaining the risks would reduce the amount of data generated
and collected.

In this context, the goal of the project is to revisit the
explanation mechanisms, often used to technically explain to
designers the key factors of a decision, to better explain to end
users which information generates more or less risk. By being
fully aware of the risk, the user can choose in full knowledge,
if he wishes to disclose such or such information. The goal
is therefore to develop explainable mechanisms to 1) clearly
inform end users about the different risks of inference, and 2)
give the user control what risk is acceptable or not to them.
If the user does not want to expose himself to a certain risk,
the data must be cleaned or sanitized to eliminate this risk of
inference.

By the way, reducing the amount of information collected
at the source (i.e., on the user side), the issues of protection
of personal data downstream are seen to be reduced and fall
within the axis of data frugality more in line with the finite
planetary resources and the environmental issues.

Mission confiée

The main mission of the postdoc will be to develop software
components to implement privacy risk analysis based on
location data directly on the mobile, collect user preferences
about the revealed information in the data, and then modify
and protect data before sharing it with third parties. In this
context, the postdoc will closely work witha PhD student on the team, who is working on a related topic.
The postdoc will also collaborate with the rest of the team, to
bring its expertise in energy consumption quantification and
in the mobile ecosystem.

Principales activités

• Implementation of PETS on mobile with a focus on location data
• Quantification of privacy risks and energy consumption on mobile with a focus on location data
• State of the art on methods in AI to generate synthetic location data
• Writingpapers / demonstration of the solutions
• Interviews and SHS stydies in relation of the developped solutions
• Participation in working groups related to team's projects
• Supervision of internships

Compétences

• 4hD in AI / Mobile / Privacy
• Fluency in English: ability to participate in complex technical discussions and argue to defend technical positions
• Interest for theprivacyregulation and for bridging technical and legal considerations

Avantages

• Restauration subventionnée
• Transports publics remboursés partiellement
• Congés: 7 semaines de congés annuels + 10 jours de RTT (base temps plein) + possibilité d'autorisations d'absence exceptionnelle (ex : enfants malades, déménagement)
• Possibilité de télétravail 90 jours/an fixes ou flottants et aménagement du temps de travail
• Équipements professionnels à disposition (visioconférence, prêts de matériels informatiques, etc.)
• Prestations sociales, culturelles et sportives (Association de gestion des oeuvres sociales d'Inria)
• Accès à la formation professionnelle
• Participation Protection Sociale Complémentaire sous conditions

Rémunération

2788€ brut/ mois

• Anglais
• Intelligence artificielle