Nhóm nghiên cứu : Phare
Ngày đi : 01-06-2018
Ban lãnh đạo nghiên cứu : Guy PUJOLLE
Un Système de Surveillance et Détection de Menaces utilisant le Traitement de flux comme une fonction virtuelle pour le Big Data
The late detection of security threats causes a significant increase in the risk of irreparable damages, disabling any defense attempt. As a consequence, fast real-time threat detection is mandatory for security guarantees.
In addition, Network Function Virtualization (NFV) provides new opportunities for efficient and low-cost security solutions. We propose a fast and efficient threat detection system based on stream processing and machine learning algorithms. The main contributions of this work are i) a novel monitoring threat detection system based on stream processing; ii) two datasets, first a dataset of synthetic security data containing both legitimate and malicious traffic, and the second, a week of real traffic of a telecommunications operator in Rio de Janeiro, Brazil; iii) a data pre-processing algorithm, a normalizing algorithm and an algorithm for fast feature selection based on the correlation between variables; iv) a virtualized network function in an open-source platform for providing a real-time threat detection service; v) near-optimal placement of sensors through a proposed heuristic for strategically positioning sensors in the network infrastructure, with a minimum number of sensors; and, finally, vi) a greedy algorithm that allocates on demand a sequence of virtual network functions.
Bảo vệ luận án : 06-06-2018 - BRESIL Hội đồng giám khảo : Mr FONSECA MAURO SERGIO PEREIRA Professeur (Rapporteur)
Mr DUARTE OTTO Professeur (Rapporteur)
Mr MACIEL KOSMALSKI COSTA LUIS HENRIQUE
Mr BATISTA DANIEL MACEDO
Mme NGUYEN Thi-Mai-Trang Maître de conférence HDR Sorbonne Université
Mr PUJOLLE Guy Professeur Sorbonne Université