Thesis of Walid Megherbi


Subject:
Anomaly detection in graph streams

Start date: 01/09/2021
Defense date: 17/04/2025

Advisor: Hamida Seba
Coadvisor: Mohammed Haddad

Summary:

Anomaly detection is a very active research area addressed by several scientific communities such as: computer security, medicine, industry and finance. In general, this problem consists of detecting data that are significantly different from benign or normal data. However, nowadays data is increasingly represented by graphs, as graphs have the ability to model complex interactions in a simple and intuitive way. The problem of detection in this case is to identify graphs that are different from the graphs corresponding to the normal objects observed by the system. In this work, we are interested in the problem of detecting anomalies in a Graph Stream.


Jury:
Mme Bonifati AngelaProfesseur(e)LIRIS - Université Claude Bernard Lyon 1Président(e)
M. Badonnel RémiProfesseur(e)TELECOM Nancy, Université de LorraineRapporteur(e)
Mme Pawlowski EstelleMaître de conférenceENSICAENRapporteur(e)
M. Couturier RaphaëlProfesseur(e)IUTBM - Université de Franche-Comté, BelfortExaminateur​(trice)
M. Benkabou Seif eddineMaître de conférenceIUT - Université de PoitiersExaminateur​(trice)
Mme Seba HamidaProfesseur(e)LIRIS Université Claude Bernard Lyon 1Directeur(trice) de thèse
M. Haddad MohammedMaître de conférenceLIRIS Université Claude Bernard Lyon 1Co-directeur (trice)