Consolidation of SIEM, SOAR and Machine Learning Technologies to Enhance the Processes of Threat Intelligence and Automated Cyber Incident Response
DOI:
https://doi.org/10.31449/upinf.155Keywords:
incident response automation, cyber threat intelligence, cybersecurity, SIEM, SOAR, machine learningAbstract
Because contemporary information systems are moving to the cloud, utilise IoT (Internet of Things) and aim to automate business processes in the context of Industry 4.0, we have to deal with big data and heavy network traffic among interconnected devices. Such amounts of data require an automated approach to the identification of anomalies, cybersecurity risks and potential cybersecurity incidents on the basis of artificial intelligence and machine learning. In this regard, especially SIEM (Security Information and Event Management) and SOAR (Security Orchestration, Automation and Response) technologies play a key role. In the paper, we explain the benefits of procedures and technologies for the automation of responses to cybersecurity incidents. We place these processes and technologies into the broader incident response approach as well as into the context of the cyber threat intelligence life cycle and use cases. We analyse the possibilities to apply, integrate and consolidate SIEM and SOAR technologies, and discuss how to use artificial intelligence and machine learning for the purpose of automated identification and orchestration of cybersecurity incidents. We review synergistic effects resulting from the integration and consolidation of SIEM, SOAR and machine learning, while we also address several organisational and technological issues, challenges and opportunities. Finally, we describe certain good practices and approaches which are being introduced within the scope of our security operations centre for the energy utilities domain.