April 18, 2024, 4:11 a.m. | Abdeljalil Zoubir, Badr Missaoui

cs.CR updates on arXiv.org arxiv.org

arXiv:2404.10800v1 Announce Type: new
Abstract: In this paper, we present two novel methods in Network Intrusion Detection Systems (NIDS) using Graph Neural Networks (GNNs). The first approach, Scattering Transform with E-GraphSAGE (STEG), utilizes the scattering transform to conduct multi-resolution analysis of edge feature vectors. This provides a detailed representation that is essential for identifying subtle anomalies in network traffic. The second approach improves node representation by initiating with Node2Vec, diverging from standard methods of using uniform values, thereby capturing a …

analysis anomaly detection arxiv cs.ai cs.cr cs.lg detection edge feature graph intrusion intrusion detection network network intrusion networks neural networks nids novel resolution systems transform

Information Security Engineers

@ D. E. Shaw Research | New York City

Technology Security Analyst

@ Halton Region | Oakville, Ontario, Canada

Senior Cyber Security Analyst

@ Valley Water | San Jose, CA

Consultant Sécurité SI Gouvernance - Risques - Conformité H/F - Strasbourg

@ Hifield | Strasbourg, France

Lead Security Specialist

@ KBR, Inc. | USA, Dallas, 8121 Lemmon Ave, Suite 550, Texas

Consultant SOC / CERT H/F

@ Hifield | Sèvres, France