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Evaluation of AI-based use cases for enhancing the cyber security defense of small and medium-sized companies (SMEs)

  • Companies are increasingly facing the challenges of a persistent cyber threat landscape. By means of AI, cyber attacks can be efficiently conducted more successful through offensive AI. As for cyber defense, AI can be also utilized against cyber threats (defensive AI). Due to limited resources, especially in small and medium-sized companies (SMEs), there is a need to deploy more effective defensive cyber security solutions. Precisely, the adaptation of AI-based resilient defenses must be drivenCompanies are increasingly facing the challenges of a persistent cyber threat landscape. By means of AI, cyber attacks can be efficiently conducted more successful through offensive AI. As for cyber defense, AI can be also utilized against cyber threats (defensive AI). Due to limited resources, especially in small and medium-sized companies (SMEs), there is a need to deploy more effective defensive cyber security solutions. Precisely, the adaptation of AI-based resilient defenses must be driven forward. Therefore, the aim of this paper is to identify and evaluate AI-related use cases with a high impact potential on the cyber security level, while being applicable to SMEs at the same time. In order to reach the research goal, an extensive literature review of several online catalogs, surveys and online platforms was conducted. In conclusion, seven crucial AI-based security features were outlined that are providing a high impact potential to the security level for SMEs. Afterwards, the results are discussed and set into a broader context. Even though AI-based security solutions are providing a large range of advantages, certain challenges and barriers using AI-related security applications are addressed in the paper as well. A high need for usable state of the art AI based cyber security solution for SMEs was identified.show moreshow less

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Metadaten
Author:Daniel Kant, Andreas Johannsen
URL:https://library.imaging.org/ei/articles/34/3/MOBMU-387
ISSN:2470-1173
Parent Title (English):Electronic Imaging
Parent Title (Multiple languages):IS&T International Symposium on Electronic Imaging : Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications, 2022
Publisher:Society for Imaging Science and Technology
Document Type:Article
Language:English
Year of Publishing:2022
Date of Publication (online):2023/10/11
Publishing Institution:Technische Hochschule Brandenburg
Release Date:2023/10/11
Volume:34
Issue:3
Article Number:387
Page Number:8
First Page:387-1
Last Page:387-8
Institutes:Fachbereich Wirtschaft
University Bibliography:Hochschulbibliografie
Licence (German):Keine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht
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