Αποτελέσματα Αναζήτησης
30 Αυγ 2023 · 1. We present a survey of graph models used to represent, store, and visualize network security data, correlating intrusion detection alerts and constructing attack scenarios. 2. We present a survey of the algorithms and approaches used to analyze such data.
30 Νοε 2018 · There is a line of research extending over the last 20+ years applying graph-based methods for assessing and improving the security of operational computer networks, maintaining situational awareness, and assuring organizational missions. This chapter reviews a...
7 Ιουλ 2023 · Network security data is intrinsically relational, and graph-structured data representations and Graph Neural Networks (GNNs) have the potential to drastically advance the AI4SEC domain. In this positioning paper we propose GRAPHSEC, a research agenda to systematically integrate GNNs in AI4SEC.
1 Ιουν 2024 · We systematically reviewed the fundamental concepts of intrusion detection and graph neural networks, then delved deeply into various aspects of applying graph neural networks to intrusion detection, including graph construction, network design, and model deployment methods.
17 Αυγ 2024 · The introduction of an attention mechanism and the construction of a Federated Graph Attention Network (FedGAT) model are used to evaluate the interactivity between nodes in the graph,...
In this paper, we review some of the key applications of graph theory in network security. We first cover some algorithmic aspects, then present network coding and its relation to routing. 1 INTRODUCTION. The rapid growth in Global mobile communication networks demands new solutions for existing problems.
15 Μαρ 2023 · This paper proposes a method of constructing knowledge graph based on network security domain ontology. Aiming at the multi-source heterogeneous network security data, extracting the association relation and designing the network security domain ontology model.
