Can AI Be Used in Cyber Security?
Cyber Security
Frazer Lloyd-Davies
Yes and in many ways, artificial intelligence already has a well-established role in cyber security. With the increasing scale and complexity of threats, conventional methods are often too slow or reactive to provide adequate protection. AI, however, can process vast volumes of data, identify patterns and respond faster than any manual process ever could.
What AI offers isn’t a replacement for human expertise but a way to reduce the risk of error and accelerate time to resolution when something goes wrong. The result is a system that can support a more resilient approach to cyber security, which is vital as cyber attacks become more targeted and sophisticated.
Below are some of the most prominent applications of AI in cyber security.
Email Threat Detection
Email is still the most common attack vector for cyber threats. Phishing, spoofing and credential harvesting often start with a single, seemingly harmless message. AI-based email security, such as that provided by Mesh Unified, assesses the structure, wording and intent behind every email. If a message pushes for urgent action involving payment or passwords, AI evaluates whether the tone and phrasing match previous legitimate communications. If it doesn’t, it’s flagged, even if the sender address appears to be trusted.
AI also analyses the behaviour of links and attachments. A link is only truly safe if it remains safe at the point of interaction, which is why Mesh Unified continues to scan emails for up to 48 hours after delivery. If an email becomes weaponised after it lands in an inbox, it can be automatically quarantined to prevent harm to the wider network.
Behaviour-Based Monitoring
Endpoint protection platforms such as SentinelOne and Huntress use machine learning, a subset of AI, to build behavioural profiles for each user and device on a network. These profiles are based on regular activity patterns like login times, file access frequency and common application use. Once a baseline is established, the system monitors for deviations.
For example, a sudden login attempt from a foreign IP address, followed by a rapid download of sensitive data, would be identified as suspicious. Even if the software being used isn’t inherently malicious, the behaviour it exhibits may indicate that a device has been compromised. This reduces the likelihood that IT teams will miss incidents that don’t follow known rules or signatures.
Response Automation and Control
AI-driven platforms, including SentinelOne, support faster incident response through automation. If a device exhibits high-risk behaviour, it can be isolated or restricted from the network to contain the threat while an engineer investigates. These actions are governed by clearly defined policies as part of a structured response plan that ensures consistency and reduces the chance of delays.
Datto Remote Monitoring and Management (RMM) helps to coordinate these efforts by providing real-time insight into device status, user behaviour and alert history. Having a unified dashboard makes it easier for IT teams to monitor and manage security events without being overwhelmed by volume or false positives.
How AI Supports Cyber Security at Acronyms
Acronyms utilises advanced AI technology across our cyber security services to proactively protect your IT network and business from the most sophisticated of attacks. The purpose of using AI is not to replace our engineers, but to assist in investigation and response. This combination of automation and human insight gives our clients the reassurance that we’ve covered all bases and have you protected on an ongoing basis.
If you have any questions about cyber security or would like to know more about the cyber security packages we offer then please book a free, no-obligation consultation.