Intelligent Detection and Recovery from Cyberattacks for Small and Medium-Sized Enterprises

Author
Keywords
Abstract
Cyberattacks threaten continuously computer security in companies. These attacks evolve everyday, being more and more sophisticated and robust. In addition, they take advantage of security breaches in organizations and companies, both public and private. Small and Medium-sized Enterprises (SME), due to their structure and economic characteristics, are particularly damaged when a cyberattack takes place. Although organizations and companies put lots of efforts in implementing security solutions, they are not always effective. This is specially relevant for SMEs, which do not have enough economic resources to introduce such solutions. Thus, there is a need of providing SMEs with affordable, intelligent security systems with the ability of detecting and recovering from the most detrimental attacks. In this paper, we propose an intelligent cybersecurity platform, which has been designed with the objective of helping SMEs to make their systems and network more secure. The aim of this platform is to provide a solution optimizing detection and recovery from attacks. To do this, we propose the application of proactive security techniques in combination with both Machine Learning (ML) and blockchain. Our proposal is enclosed in the IASEC project, which allows providing security in each of the phases of an attack. Like this, we help SMEs in prevention, avoiding systems and network from being attacked; detection, identifying when there is something potentially harmful for the systems; containment, trying to stop the effects of an attack; and response, helping to recover the systems to a normal state.
Year of Publication
2020
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
6
Issue
Special Issue on Artificial Intelligence and Blockchain
Number
3
Number of Pages
55-62
Date Published
09/2020
ISSN Number
1989-1660
URL
https://www.ijimai.org/journal/sites/default/files/2020-08/ijimai_6_3_7.pdf
DOI
10.9781/ijimai.2020.08.003
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