On the Provision of Network-Wide Cyber Situational Awareness via Graph-Based Analytics

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Publikace nespadá pod Filozofickou fakultu, ale pod Ústav výpočetní techniky. Oficiální stránka publikace je na webu muni.cz.
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HUSÁK Martin KHOURY Joseph KLISURA ?orđe BOU-HARB Elias

Rok publikování 2023
Druh Článek ve sborníku
Konference Complex Computational Ecosystems
Fakulta / Pracoviště MU

Ústav výpočetní techniky

Citace
www https://link.springer.com/chapter/10.1007/978-3-031-44355-8_12
Doi http://dx.doi.org/10.1007/978-3-031-44355-8_12
Klíčová slova Cyber security;Cyber situational awareness;Graph-based analytics;Large and complex network;Network security management
Přiložené soubory
Popis In this paper, we posit how semi-static (i.e., not changing very often) complex computer network-based intelligence using graphbased analytics can become enablers of Cyber Situational Awareness (CSA) (i.e., perception, comprehension, and projection of situations in a cyber environment). A plethora of newly surfaced cyber security researchers have used graph-based analytics to facilitate particular down tasks in dynamic complex cyber environments. This includes graph-, node- and edge-level detection, classification, and others (e.g., credit card fraudulent transactions as an edge classification problem). To the best of our knowledge, very limited efforts have consolidated the outputs of heterogeneous computer network monitoring and reconnaissance tools (e.g., Nmap) in enabling actionable CSA. As such, in this work, we address this literature gap while describing several use cases of graph traversal, graph measures, and subgraph mining in vulnerability and security state assessment, attack projection and mitigation, and device criticality estimation. We highlight the benefits of the graph-based approaches compared to traditional methods. Finally, we postulate open research and application challenges in graph-based analytics for CSA to prompt promising research directions and operational capabilities.
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