Use AI to detect vulnerabilities before hackers do

How does AI work in cybersecurity?

AI uses machine learning models to analyse patterns in data and identify abnormal activities, which may indicate cyberattacks. By learning from previous data on known threats, AI systems can also predict new, unknown attacks, making AI effective in guarding against emerging methods of attack.  

This is achieved through techniques such as: 

• Anomaly detection: AI continuously monitors network traffic, searching for unusual patterns, such as a user suddenly accessing large amounts of data or attempting logins from unexpected locations. 

• Behavioural analysis: By analysing employee behaviour, AI can detect suspicious activity. If an employee's account suddenly behaves unusually, like accessing systems outside normal hours, AI can alert potential security breaches. 

• Prediction of new threats: AI can analyse large datasets to identify early signs of new attack methods not yet widely known, enabling organisations to strengthen their defenses before the attacks become widespread. 

Enhanced threat identification

One of the most notable benefits of AI is its ability to analyse data in real time and respond swiftly to potential threats. 

Instead of waiting for cybersecurity experts to manually detect an attack, AI can instantly alert to irregularities and even actively halt attacks before they cause harm. This includes: 

• Automation of security incidents: When AI systems detect a threat, they can automatically initiate security protocols, such as locking a compromised account or blocking suspicious network traffic. 

• Real-time threat detection: By constantly analysing behaviour and network activity, AI can detect and respond to attacks, even outside working hours or at times when human employees may be unable to detect them. 

AI’s role in proactive security

Traditionally, many cybersecurity strategies have been reactive, responding to attacks after they occur. AI enables a more proactive approach by identifying potential vulnerabilities before they are exploited. 

For example, AI can identify software vulnerabilities by analysing source code to detect flaws that hackers might exploit. By predicting these vulnerabilities, companies can fix them before hackers have a chance to exploit them. 

By analysing data from past attacks, AI can also predict future threats, allowing cybersecurity teams to better prepare and establish measures before new attacks strike.