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

Liam Randall

Participant

President, Critical Stack, A Division of Capital One

Chad Skipper

Participant

Global Security Technologist, VMware

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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