Peter Cox, Inventor and CEO at UM-Labs R&D has moved LEM-AI to the next level, hear about this first hand at the AI -World Congress in London on the 19th June 2025

As cyber threats increasingly target real-time communications and grow ever more sophisticated, traditional security measures are no longer sufficient. The UM-Labs AI Large Event Model (LEM) introduces a revolutionary approach to cybersecurity for real-time traffic by leveraging AI-powered threat detection, predictive intelligence, and automated response mechanisms. With over a decade’s worth of cyber-attack data contained in SNITCH Event Database, the model has the historical data to help anticipate future threats and thus offers the potential to deploy pre-emptive defences. The scalable and adaptable architecture ensures that security measures can be effectively implemented across diverse network environments, providing a robust and dynamic cybersecurity solution. By harnessing AI-driven analytics, cross-domain correlation, and automated threat mitigation, the UM-Labs LEM sets a new standard in proactive cybersecurity, enabling organisations to stay ahead of evolving threats and secure real-time communications more effectively than ever before.

Large Event Model, An Alternative AI Model for Analysing Attacks on Structured Network Protocols | AI Conference London 2025

SNITCH Attack Intelligence   +++  2,062,922 attacks from 198.12.105.178, location United States    +++  122,803 attacks from 81.7.11.179, location Germany    +++  886 attacks from 5.196.203.196, location Spain    +++  450 attacks from 69.175.4.222, location United States    +++  277 attacks from 193.46.255.235, location United Kingdom    +++  New attack source, United States, 104.168.81.198     +++  New attack source, Hong Kong, 103.176.90.231     +++  New attack source, Hong Kong, 103.176.90.92  
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