Any recommendations you can share for evaluating or implementing AI-driven network detection and response (NDR)?

Machine Learning (ML)Artificial Intelligence (AI)

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CISO and Head of Digital Channels in Healthcare and Biotech5 months ago

Your focus on integration efficacy and visibility is spot-on—these are foundational to NDR success. Below are expanded recommendations to ensure a robust implementation:

Integration & Actionability:
Test automated blocking with existing tools (EDR, firewalls) via attack simulations.
Demand vendor data on false positives/negatives, especially for encrypted traffic.
Visibility:
Verify coverage for all environments (cloud, IoT, legacy) and protocols. Specifically if your company has units in different physical locations that influences the IT infrastructure.
Scalability:
Stress-test throughput (e.g., 100Gbps+) and NDR behavior in peak conditions (if the tool is not loosing packets).

CIO in Banking5 months ago

The key success factor is to master the basics , eliminate all blind spots , and connect your NDR to the cybersecurity ecosystem , such as SIEM and SOAR, perform continuous tuning, eliminate noise , and develop your own use cases .

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