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   +++  27,736,674 attacks from 103.176.90.16, location Hong Kong    +++  80,025 attacks from 94.23.161.138, location Germany    +++  4,003 attacks from 193.46.255.142, location United Kingdom    +++  3,903 attacks from 173.231.185.164, location United States    +++  1,745 attacks from 92.205.110.66, location France    +++  483 attacks from 216.9.227.134, location Türkiye    +++  New attack source, United States, 198.235.24.135     +++  New attack source, United Kingdom, 80.94.93.158  
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