Evaluating AI- and ML-Based Security Products


Posted on in Presentations

With endless AI or machine learning product claims, buyers are left bewildered with how to test these claims. It falls to independent third-party test organizations to develop and update traditional test protocols to test and validate AI and ML product capability claims. This panel will tackle the key issues that third-party testing must address to validate AI and ML security products.

Learning Objectives:
1: Learn to identify gaps in traditional testing approaches for AI/ML-based products.
2: Explore new approaches for testing AI/ML products.
3: Hear arguments for standards bodies and test organizations to upgrade test approaches.

Participants
Anup Ghosh

Participant

Founder and CEO, Invincea

Chad Skipper

Participant

VP Competitive Intelligence and Product Testing, Cylance

Liam Randall

Participant

President, Critical Stack, A Division of Capital One

Mike Spanbauer

Participant

Vice President of Research and Strategy, NSS Labs

Analytics Intelligence & Response Security Strategy & Architecture

big data analytics governance risk & compliance artificial intelligence & machine learning


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