Machine Learning in Cybersecurity: 5 Real-Life Examples

Hacker Noon


From real-time cybercrime mapping to penetration testing, machine learning has become a crucial part of cybersecurity. Fortunately, machine learning can help solve the most common tasks, including pattern detection, prediction, regression, and classification.

In an era of large amounts of data and a shortage of network security talents, machine learning seems to be an alternative to solve many problems. Indeed, through machine learning, when applied to computer security, we can sort through millions of files to discover threats. Microsoft Windows Defender, for example, employs multiple layers of machine learning to block potential threats.

Here are a few ways cybersecurity uses machine learning.

1. Signature-based Threat Detection

In computer security, old-fashioned threat detection systems use heuristic and static signatures to detect...

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