TY - JOUR
T1 - A Taxonomy for Large-Scale Cyber Security Attacks
AU - Mohsen, Fadi
AU - Zwart, Cornelis
AU - Karastoyanova, Dimka
AU - Gaydadjiev, Georgi
PY - 2022/3/1
Y1 - 2022/3/1
N2 - In an effort to examine the spread of large-scale cyber attacks, researchers have created various taxonomies. These taxonomies are purposefully built to facilitate the understanding and the comparison of these attacks, and hence counter their spread. Yet, existing taxonomies focus mainly on the technical aspects of the attacks, with little or no information about how to defend against them. As such, the aim of this work is to extend existing taxonomies by incorporating new features pertaining the defense strategy, scale, and others. We will compare the proposed taxonomy with existing state of the art taxonomies. We also present the analysis of 174 large cyber security attacks based on our taxonomy. Finally, we present a web tool that we developed to allow researchers to explore exiting data sets of attacks and contribute new ones. We are convinced that our work will allow researchers gain deeper insights into emerging attacks by facilitating their categorization, sharing and analysis, which results in boosting the defense efforts against cyber attack.
AB - In an effort to examine the spread of large-scale cyber attacks, researchers have created various taxonomies. These taxonomies are purposefully built to facilitate the understanding and the comparison of these attacks, and hence counter their spread. Yet, existing taxonomies focus mainly on the technical aspects of the attacks, with little or no information about how to defend against them. As such, the aim of this work is to extend existing taxonomies by incorporating new features pertaining the defense strategy, scale, and others. We will compare the proposed taxonomy with existing state of the art taxonomies. We also present the analysis of 174 large cyber security attacks based on our taxonomy. Finally, we present a web tool that we developed to allow researchers to explore exiting data sets of attacks and contribute new ones. We are convinced that our work will allow researchers gain deeper insights into emerging attacks by facilitating their categorization, sharing and analysis, which results in boosting the defense efforts against cyber attack.
U2 - 10.4108/eai.2-3-2022.173548
DO - 10.4108/eai.2-3-2022.173548
M3 - Article
SN - 2410-6895
VL - 7
JO - EAI Endorsed Transactions on Cloud Systems
JF - EAI Endorsed Transactions on Cloud Systems
M1 - e5
ER -