The Zero Trust security model assumes a hostile network with relentless external and internal threats. Authenticating and authorizing every device, user and network flow requires real-time algorithmic processing of telemetry from as many sources of data as possible. Applying mature machine learning data science to the Zero Trust problem provides a wholistic solution to multiple domains of security – changing the game for security architects and operations. This session reviews Zero Trust principles and proposes an AI approach to operationalizing the model.
