HUSÁK, Martin, Mohamed-Lamine MESSAI and Hamida SEBA. The 5th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2024). 2024.
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Basic information
Original name The 5th International Workshop on Graph-based Approaches for CyberSecurity (GRASEC 2024)
Authors HUSÁK, Martin (203 Czech Republic, guarantor, belonging to the institution), Mohamed-Lamine MESSAI and Hamida SEBA.
Edition 2024.
Other information
Original language English
Type of outcome Organization of a workshop
Field of Study 10200 1.2 Computer and information sciences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Organization unit Institute of Computer Science
Keywords in English cybersecurity;network security;graph theory;knowledge graph;GNN
Tags International impact
Changed by Changed by: RNDr. Martin Husák, Ph.D., učo 256631. Changed: 5/8/2024 11:12.
Abstract
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.
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