Machine learning is a process of teaching computers to learn from data, identify patterns and make predictions. It is being used in a variety of ways to improve cybersecurity, including:
- Identifying cyber threats: Machine learning can be used to analyse huge amounts of data to identify patterns that may indicate a cyber attack.
- Blocking attacks: Once a potential attack has been identified, machine learning can be used to block it before it happens.
- Improving security systems: Machine learning can be used to constantly test and improve security systems, making them more effective at stopping attacks.
- Helping humans: Machine learning can be used to help human security analysts by providing them with information about potential threats.
Example of Machine Learning in Cybersecurity?
One example of machine learning being used in cybersecurity is its ability to identify patterns in data that may indicate a cyber attack. By analyzing huge amounts of data, machine learning can spot patterns that humans may not be able to see. This can help to prevent attacks before they happen.