Subject: cybersecurity exercises
Subject: cybersecurity training platforms taxonomy
Subject: training
Year: 2020
Type: Article
Title: Cybersecurity Training Platforms Assessment
Author: Kjorveziroski, Vojdan
Author: Mishev, Anastas
Author: Filiposka, Sonja
Abstract: Hands-on experience and training related to the latest cyberthreats and best practices, augmented with real-life examples and scenarios is very important for aspiring cybersecurity specialists and IT professionals in general. However, this is not always possible either because of time, financial or technological constraints. For cybersecurity exercises to be effective they must be well prepared, the necessary equipment installed, and an appropriate level of isolation configured, preventing inter-user interference, and protecting the integrity of the platform itself. In recent years there have been numerous cybersecurity training systems developed that aim to solve these problems. They can either be used as cloud or self-hosted applications. These solutions vary in their level of sophistication and ease-of-use, but they all share a single goal, to better educate the cyber community about the most common vulnerabilities and how to overcome them. The aim of this paper is to survey and analyze popular cybersecurity training systems currently available, and to offer a taxonomy which would aid in their classification and help crystalize their possibilities and limitations, thus supporting the decision-making process.
Publisher: Springer Nature
Relation: ICT Innovations 2020. Machine Learning and Applications
Identifier: oai:repository.ukim.mk:20.500.12188/30107
Identifier: Kjorveziroski, V., Mishev, A., Filiposka, S. (2020). Cybersecurity Training Platforms Assessment. In: Dimitrova, V., Dimitrovski, I. (eds) ICT Innovations 2020. Machine Learning and Applications. ICT Innovations 2020. Communications in Computer and Information Science, vol 1316. Springer, Cham. https://doi.org/10.1007/978-3-030-62098-1_15Identifier: http://hdl.handle.net/20.500.12188/30107Identifier: 10.1007/978-3-030-62098-1_15
