Imran Khan shares insights on risk-based scoping of critical assets, network segmentation for granular workflow policies, identity micro-classification for authentication, and quarantine subnets isolating non-compliant devices for automated patching.
The accelerating adoption of artificial intelligence by threat actors represents a paradigm shift in the cyberthreat landscape, rendering traditional perimeter-based security models fundamentally obsolete. AI-powered attacks leverage automated vulnerability discovery, hyper-realistic social engineering (e.g., deepfake phishing), and adaptive malware that can learn to evade static defenses.
Effective zero trust starts with risk-based scoping of critical assets rather than attempting to secure entire networks simultaneously.
In this session, Imran Khan of BNP Paribas will share insights on:
- Network segmentation as the enforcement point for granular policies targeting specific workflows such as claims processing;
- Identity micro-classification distinguishing admin rights, power users and non-human accounts requiring different authentication policies and access controls;
- Quarantine subnets isolating non-compliant devices for automated patching with alerts when legacy systems cannot update.
Here is the course outline:
From Perimeter to Policy: A Zero Trust Implementation Case Study |
Completion
The following certificates are awarded when the course is completed:
 |
CPE Credit Certificate |
