Podrobný výpis o publikaci

HUSÁK, Martin, Mohamed-Lamine MESSAI a Hamida SEBA. The 5th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2024). 2024.

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TY  - CONF
ID  - 2420897
AU  - Husák, Martin - Messai, Mohamed-Lamine - Seba, Hamida
PY  - 2024
TI  - The 5th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2024)
KW  - cybersecurity;network security;graph theory;knowledge graph;GNN
UR  - https://www.ares-conference.eu/grasec
N2  - 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 promising strategy that is gaining more and more attention these last years. It is becoming more and more usual to employ graph databases and graph mining and learning algorithms for processing massive and complex data. 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, which can be achieved using a graph to represent particular events and observations and relations between them. 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, data science, 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.
ER  -

Základní údaje
Originální název	The 5th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2024)
Autoři	HUSÁK, Martin (203 Česká republika, garant, domácí), Mohamed-Lamine MESSAI a Hamida SEBA.
Vydání	2024.

Další údaje
Originální 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
WWW	URL
Organizační jednotka	Ústav výpočetní techniky
Klíčová slova anglicky	cybersecurity;network security;graph theory;knowledge graph;GNN
Příznaky	Mezinárodní význam
Změnil	Změnil: RNDr. Martin Husák, Ph.D., učo 256631. Změněno: 5. 8. 2024 11:12.

Anotace
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 promising strategy that is gaining more and more attention these last years. It is becoming more and more usual to employ graph databases and graph mining and learning algorithms for processing massive and complex data. 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, which can be achieved using a graph to represent particular events and observations and relations between them. 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, data science, 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.

Anotace

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 promising strategy that is gaining more and more attention these last years. It is becoming more and more usual to employ graph databases and graph mining and learning algorithms for processing massive and complex data. 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, which can be achieved using a graph to represent particular events and observations and relations between them. 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, data science, 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.