Techniques for Automatic Device Identification and Network Assignment
summary
Claims an operational path: consolidate fragmented inventories into a single database that reduces 128-column scan outputs with 60+ blank fields to actionable records, deploy AI models that perform auto-identification and classification of millions of devices, apply real-time CVE application to tag risk scores and trigger isolation, and map devices by quantum-readiness for future crypto. Built outcome is automated registration, dashboards showing compliant vs noncompliant counts, and faster SOC response to compromised endpoints.
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chapters (13)
- 0:00Device identification challenges
- 2:36Inventory and resource allocation
- 4:02Unknown and IoT devices at scale
- 8:57Quantum readiness and controls
- 12:49Automating policies with AI
- 19:24Discovery and collaboration
- 23:27Consulting and risk matrix
- 27:44AI for threat intelligence
- 31:03Zero trust and compliance
- 33:48Measuring compliance and risk
- 37:27Tracking progress and improvement
- 40:22Next steps and coordination
- 41:04Q&A
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