W 2023

The 4th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2023)

HUSÁK, Martin, Mohamed-Lamine MESSAI a Hamida SEBA

Základní údaje

Originální název

The 4th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2023)

Autoři

HUSÁK, Martin (203 Česká republika, garant, domácí), Mohamed-Lamine MESSAI a Hamida SEBA

Vydání

2023

Další údaje

Jazyk

angličtina

Typ výsledku

Uspořádání workshopu

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Kód RIV

RIV/00216224:14610/23:00131658

Organizační jednotka

Ústav výpočetní techniky

Klíčová slova anglicky

graph;graph theory;cybersecurity;network security;intrusion detection

Štítky

Příznaky

Mezinárodní význam
Změněno: 20. 3. 2024 14:27, RNDr. Martin Husák, Ph.D.

Anotace

V originále

The complexity of today’s systems and the data they produce has made it more difficult to ensure their security due to the data overload, the need to store and handle massive amounts of data, and efficient analysis. Using graphs and knowledge graphs to analyze and interpret the data is a very intriguing strategy that is gaining more and more attention these days. It is becoming more and more usual to employ graph databases, graph mining and learning algorithms, and tools for processing massive volumes of data using graphs. Graphs, including complex networks and knowledge graphs, offer the advantage of capturing complex and heterogeneous systems and activities. Moreover, the visualization of graph-based data is straightforward and comprehensible for human analysts, which makes it very powerful in practice. For example, Botnet activity can be observed as a plethora of observables, and there is a need to correlate the particular observations into a big picture, such as using a graph to represent particular events and observations and relations between them. The attack graphs are popular tools for representing cyber attacks, calculating their impact, and even projecting them and predicting the next step of an adversary. This workshop aims at bringing together people from industry and academia, including researchers, developers, and practitioners from a variety of fields working on graphs and knowledge graphs, network management, and cybersecurity. The workshop will allow attendees to share and discuss their latest findings from both theoretical and practical perspectives, namely in terms of graph-based security data representation, analysis, processing and visualization. The workshop attendees may benefit from sharing experience on graph-based data analysis regardless of the specific application. Moreover, researchers and practitioners will have an opportunity to familiarize themselves with recent advances in graph analysis, mining and learning, and other approaches that could be used in their work. The workshop aims to highlight the latest research and experience in graph-based approaches in cybersecurity. The workshop also seeks papers describing new datasets with real attack scenarios, graph modeling tools evaluated on existing and proposed datasets, and systematization of knowledge (SoK) papers.