Using artificial intelligence and machine learning to detect abnormal behavior

Computers can be programmed to calculate probabilities and take actions based on the result to recreate human intelligence. This is the base on which technologies like artificial intelligence and machine learning are built.

What is artificial intelligence (AI)?

AI is the concept of programming a computer to solve problems on its own by applying cognitive traits of humans such as the ability to learn, understand, reason, and remember from experience. AI systems can combine information from a variety of different sources, correlate the data, and act on the insights derived from the data.

What is machine learning (ML)?

ML is a subset of AI that trains a computer to learn and make decisions without being programmed explicitly for each scenario. It uses AI algorithms to learn from existing data and past experiences to improve itself. ML models also look for patterns in data and try to draw conclusions. This conclusion can then lead to a suitable workflow.

How are AI and machine learning used in cybersecurity?

AI and ML have a huge significance in cybersecurity. AI is great at distinguishing normal and anomalous behavior. By implementing ML, computer systems can be programmed to train themselves to improve their ability to detect unfamiliar security anomalies and deviant behavior. Using these techniques in cybersecurity greatly improves the accuracy of detecting threats. Moreover, ML models can perform preliminary inquiries on detected threats, and cut down a significant number of false positives that occur in security systems.

In a business environment, security information and event management (SIEM) systems equipped with AI and ML can effectively arrange the threat detection workflows in your network.