USING MACHINE LEARNING (ML) TO DETECT THREAT ANOMALIES FOR REDUCING FALSE-POSITIVES ON THE DAILY CYBERSECURITY OPERATION CENTRE ROUTINE

Petro Venherskyi, Roman Karpiuk

Анотація


With machine learning, we are able to detect a variety of cybersecurity threats, such as brute force, abnormal growth or decline in network traffic, monitor end-user infections with malware, or detect attacks on critical infrastructure, such as AD, DNS. The main advantage of using ML for such scenarios is the accuracy of detection of certain anomalies. This, in turn, significantly reduces the financial cost of cybersecurity in the organization and the speed of countering attackers.

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DOI: http://dx.doi.org/10.30970/vam.2021.29.11339

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