Offre en lien avec l’Action/le Réseau : – — –/Doctorants

Laboratoire/Entreprise : DVRC (ALDV) / Cedric (Cnam) / Kwanko
Durée : 36 mois
Contact : nicolas.travers@devinci.fr
Date limite de publication : 2020-10-31

Contexte :
The world of digital marketing through Real Time Bidding (RTB) is based on tracking and analyzing user behavior on the web. With users tracking on the web via their interactions on web browsers, smartphones, emails or advertisements, RTB seeks to maximize the dissemination of information on the Web. Thus, by following the digital journey of the user, the RTB adapts the advertising campaigns to their profiles. With the arrival of the GDPR (General Data Protection Regulation), data confidentiality becomes a major issue for companies working in e-commerce. Having to manage user profiles and preserve their privacy adds complexity that goes against the principle of traditional user tracking [1,2,3]. It then becomes necessary to define user profiles adapted to the new standards and thus produce ethical tracking.
In addition, the traffic generated by the RTB process has a huge impact on the consumption of resources, both on the network, the computing servers, and in the user’s environment. Recently, the theme of responsible marketing or ecodesign of media supports (Green Design) is emerging [4,5], but the RTB field is still slow to evolve on these modular conceptions of the tracking and analysis process.
Thus, the possibility of marrying RTB with Green Design then becomes a strong argument in an advertising campaign. Kwanko seeks to meet these two challenges by adapting their RTB processes. Founded in 2003, Kwanko is a major player in performance digital advertising on the Web, mobile and tablets. Its purpose is to support advertisers in the context of traceability and maximizing the impact of their advertising campaigns. Kwanko makes it easier for brands to connect with their audiences on the web. The problem addressed in this research subject is multiple. In the context of maximizing the impact of an RTB campaign, we must both preserve the possibility of tracking users to maximize the “transformation” (optimal tracking), minimize the energy impact of the analysis process and tracking (responsible tracking) and maximizing the protection of the user’s privacy (ethical tracking). This problem combines opposite dimensions implying a problem of multi-stress maximization.

This doctoral thesis will be funded by a CIFRE contract with Kwanko, in partnership with the DVRC laboratory of the Leonardo da Vinci Association (Paris La Défense) within the digital group, supervised by Nicolas Travers (HDR) and Cédric du Mouza (HDR).

Sujet :
Towards responsible digital traces
In the first part, we plan to redefine the tracking and analysis process in modular microcomponents [3]. The idea is to dissociate personal data from the analysis by producing an adaptive data model that will serve as a common model for the analysis steps. The separation into microcomponents makes it possible to quantify the energy impact of each component and thus to optimize it to reduce the cost. First, the complexity of the processing performed in each component associated with the amount of data to be processed (depending on the user profile) gives the cost of each step of the analysis. The combination of microcomponents based on unit operations produces an algebraic expression whose operations are interchangeable for optimization. The overall complexity of the algebraic expression thus gives the energy impact of the RTB analysis. To reduce the energy impact, an initial heuristic will try to allocate the task to the optimal location to reduce the overall impact, either by pooling multi-campaign calculations, or by pooling user profiles. The relevance of a campaign with the user profile can be calculated both on the browser and on the server.

Towards ethical digital traces
In the second step, we will rely on the common data model that will be used in the tracking process to preserve the user profile. The aim is to reduce the dependence of classical analysis models on user profiles, amplified by the tendency to block these trackers [6]. Thus, we will be able to manage the cursor between the precision of the analysis according to the users’ adherence to profiling, tending towards an ethical tracking. Like visual tracking techniques [7], privacy preservation strategies are based on the definition of activity patterns for the detection of specific patterns (Activity Pattern Detection). It is possible to orient our data model in the form of Activity Pattern for RTB. The profile will be analyzed in the user area to generate local detections based on a dedicated campaign. The result then produces a recommendation to target the user with relevant advertising while maximizing privacy protection. Another option being considered is to use techniques to define a multidimensional targeting model for campaigns and to place the user in it. In order to guarantee its anonymization, we will move towards random allocation techniques with probabilistic guarantee as used in the secure allocation of requests preserving privacy [8]. This approach will allow the user profile to be projected onto campaign profiles and to target the user without knowing the user.

Towards an optimal digital trace calculation
The cost model based on energy impact will therefore be based on the complexity of the components, their combination for analysis, the level of privacy protection, the amount of data available, and the level of precision expected at output. Multi-criteria optimization is therefore necessary to guide the choice of the analysis solution suitable for a set of advertising campaigns. The idea for Kwanko is to offer a service that can be adapted to their client by trying to respond to different dimensions of tracking that are hardly compatible: ethical, responsible and optimal. The customer will be able to accentuate a dimension according to the impact he wishes to have in his campaign.

Profil du candidat :
holder of Master in IT, with solid knowledge in data distribution, pattern mining, possibly secure data processing, but also a strong experience in development is recommended

Formation et compétences requises :
BAC+5 Computer Science – DBMS / distributed systems / IS

Adresse d’emploi :
Kwanko 60 BD DU MARECHAL JOFFRE 92340 BOURG-LA-REINE
DVRC Pôle Universitaire Léonard de Vinci 92 916 Paris La Défense Cedex

Document attaché : 202009081502_PHD_Kwanko.docx