<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/334791D3-BC1D-47EA-B32F-9FF7C32F6C0A" ns1:id="334791D3-BC1D-47EA-B32F-9FF7C32F6C0A"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/96F0781F-F31A-4D5D-B2D1-78E22F494063" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5F8915AC-8108-45EC-817D-E0123EFD9E9E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/5F8915AC-8108-45EC-817D-E0123EFD9E9E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/51111C90-762F-485C-8322-CD163425DE64" ns1:rel="FUND" ns1:start="2024-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10139586</ns2:identifier></ns2:identifiers><ns2:title>CyberMATI : AI-Solution for Detecting Zero-Day Phishing Attacks</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>CyberMATI is an innovative cybersecurity project designed to protect against phishing attacks, a common and dangerous type of online scam. Phishing attacks trick people into sharing sensitive information---like passwords or credit card details---by disguising fake websites as trusted ones, such as those of banks or well-known companies. These scams can lead to serious financial losses and data breaches.

What makes CyberMATI stand out is its ability to combat the most difficult phishing threats---those that exploit unknown security gaps. These &amp;quot;zero-day&amp;quot; attacks involve newly created phishing sites that traditional security systems can't yet recognize, making them especially harmful.

While most current anti-phishing methods focus on checking web addresses or analysing website content, these approaches struggle to spot new phishing sites that can quickly change how they look. CyberMATI takes a different approach by focusing on a website's visual appearance rather than its underlying content or code. Our patent-pending solution uses AI to analyse the visual features of websites in real-time, detecting fake sites that mimic legitimate ones before they can cause harm.

At this stage, funding is crucial to refine our solution and fully develop a prototype that can be tested in real-world settings. This investment will help us move CyberMATI forward, ensuring it becomes a reliable tool for businesses and organizations in need of stronger protection against evolving online threats.</ns2:abstractText></ns2:project>