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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F23%3A00130688" target="_blank" >RIV/00216224:14610/23:00130688 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-031-44355-8_12" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-44355-8_12</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-44355-8_12" target="_blank" >10.1007/978-3-031-44355-8_12</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10200 - Computer and information sciences

Project

<a href="/en/project/EH22_010%2F0003229" target="_blank" >EH22_010/0003229: MSCAfellow5_MUNI</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Complex Computational Ecosystems

ISBN

9783031443541

ISSN

0302-9743

e-ISSN

—

Number of pages

13

Pages from-to

167-179

Publisher name

Springer Nature

Place of publication

Cham, Switzerland

Event location

Baku

Event date

Apr 25, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—