We’re all seeing what AI can do, and we’re at various stages of adoption. But cutting across the noise of the “concept”, how can AI tangibly make your business more secure?

Threat detection and intelligence are crucial functions of security. They overlap and feed each other, but they are separate entities with distinct functions. Incident response (IR) is another aspect, which will be discussed in a separate article.

So where is AI most powerful?

There are four big things going on in your threat detection and intelligence systems:

Predictive analytics: This operation attempts to predict future threats by analysing historical threat data using Machine Learning (ML) to learn from large datasets and identify complex patterns. GenAI contributes to predictive analytics by using historical and synthetic (fake) data to simulate future attack scenarios. This is useful for predicting future threat vectors and anticipating attack trends.

Behavioural analytics: This is like predictive analytics but is focused on user behavior. Unusual user behaviour may reveal potential threats that standard security protocols miss. Machine learning automates the data analysis and identifies anomalies that might indicate a security threat. These anomalies could be very subtle and easily missed in manual reviews. GenAI models normal and abnormal behaviors to improve the analysis and better distinguish between harmless and malicious activities. Behavioral analytics help detection systems identify insider threats and identify compromised accounts.

Anomaly detection: This component monitors the network for unusual patterns or behaviors that deviate from the norm. ML improves the system by learning from known data and adjusting to new types of anomalies over time. GenAI creates synthetic anomalies to improve detection models and make the system more resilient to new threats. Zero-day attacks and unusual login patterns might be detected here.

Pattern recognition: As you may expect, this identifies regular patterns or structures in data, which helps classify and detect known types of cyberthreats. Machine learning automates this process and improves the accuracy of recognition. GenAI creates new patterns of attack simulations to improve learning. This may be used to classify types of malware, identify threat actor relationships, or recognise spear-phishing campaigns.

Want to learn more?

Complete IT Systems have a team of Barracuda specialists on hand to demo the solution, discuss business benefits and help you understand how the technology works for your organisation.

To get in touch or request a demo please contact us.

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