Securing Algorithms for Classification and

il y a 1 semaine

Versailles, France INRIA Temps plein

**PhD Position F/M**:
**Securing Algorithms for Classification and Machine Learning on Personal Data using Trusted Execution Environments**

**Supervision **:Iulian Sandu Popa (Iulian.Sandu-Popa at uvsq.fr), Nicolas Anciaux (Nicolas.Anciaux at inria.fr)

**Context.**

**Objectives of the thesis.**

Thesis objectives. The targeted approach leads to a paradigm shift, as the processing code on user data comes to the data and not the other way around. However, this does not guarantee secure processing. The aim of this thesis is to design and implement strategies for running personal data classification and learning algorithms, while guaranteeing each user participating in the computation with her data an upper bound on the potential leakage of data concerning her (quantifiable as a function of the type of computation, the data,...) during the computation. Preliminary work has made it possible to guarantee mínimal leakage when running simple statistics (sum or average) on a single user's data [3,4]. The aim of this thesis will be to propose and implement solutions for processing complex data (such as images) and advanced processing such as classification and learning algorithms, on populations of users.

This thesis takes place within the framework of the PEPR (Priority Research Program and Equipment) Cybersecurity iPoP (interdisciplinary Project on Privacy) project involving several internationally recognized French research teams working on data protection, from universities, engineering schools and national research organizations, as well as the CNIL (French National Commission on Information Technology and Civil Liberties).

**Profile and skills required.**
- data management systems, classification techniques, machine learning techniques;
- Interest in system aspects, privacy, security and trusted environments;
- programming : C, C++, system : linux (administration, scripting);
**Benefits package**
- subsidized meals, Partial reimbursement of public transport costs
- leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (ill children, moving home, etc.)
- possibility of teleworking and flexible organization of working hours
- social, cultural and sports events and activities
- access to vocational training

**Remuneration**
- 1st and 2nd year monthly gross salary : 2.051 euros
- 3rd year monthly gross salary : 2.158 euros

**References.**

[2] Nicolas Anciaux, Luc Bouganim, Philippe Pucheral, Iulian Sandu Popa, Guillaume Scerri. « Personal Database Security and Trusted Execution Environments: A Tutorial at the Crossroads ». Tutorial at PVLDB 12(12), 2019.

Type d'emploi : Temps plein, CDD
Durée du contrat : 36 mois

Salaire : 2 051,00€ par mois

Avantages:

- Formation linguistique offerte
- Horaires flexibles
- Prise en charge du transport quotidien
- Restaurant d'entreprise
- RTT
- Travail à domicile

Exigences linguistiques flexibles:

- Français non requis

Programmation:

- Du lundi au vendredi
- Horaires flexibles
- Période de travail de 8 Heures

Formation:

- Bac +5 (Master / MBA) (Exigé)

Lieu du poste : En présentiel

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