How AI is Transforming Network Security and User Experience
summary
Palo Alto Networks and Major League Baseball describe a SASE build that fuses network and security telemetry into one data lake meeting the three Cs: complete, consistent, correct, uses inline ML to stop 95% of zero day threats, and pushes 4.3 million updates per day, claims seeing a trillion threats weekly. Examples include ML URL filtering, contextual DLP that detects Slack passcode sharing, SD‑WAN that runs with zero routing protocols across 4,000+ customers, and LLMs that cut demo lab setup from months to an afternoon.
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chapters (12)
- 0:00Start
- 3:06Security Model Pre-Hybrid Work
- 7:35Previously the Access Model Was Fragmented
- 9:15Customer Projects Driving ZTNA/SASE
- 16:37Al-Powered SASE Unlocks the Power of Data
- 19:27The Threat Landscape Is Evolving
- 20:41Scale Required for Al-Powered Security
- 21:30Stopping Unknown Attacks with ML
- 24:15Defending Against Phishing Attacks with ML
- 25:14Al-Powered Data Loss Prevention
- 27:35Enabling Zero Trust for the Branch of the Future
- 30:05Deep Observability of Everything Impacting User Experience
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