Creating Trustworthy AI Frameworks for Federal Healthcare Applications

Date: July 21 | 01:00 PM ET

Recent security-related events, particularly ransomware attacks, have exposed vulnerabilities in the Federal Government’s data security and have put some of our nation’s most critical healthcare information at risk. A large element in modern cybersecurity that is being overlooked, are the attacks on AI and ML environments, however a very small percentage of current AI research goes towards defending AI systems against these adversarial efforts.

Why Attend:
In this security-focused event, we’ll defining and evaluating AI/ML threat vectors, translate security requirements into actionable responses, learn about protecting against adversarial AI/ML Attacks:
At Rest, In Motion, During Processing and how to build an infrastructure to implement security strategies.

During this 1-hour webcast you will learn about:
  • Defining and Evaluating AI/ML Threat Vectors
  • Translating Security Requirements into Actionable Responses
  • Protecting Against Adversarial AI/ML Attacks: At Rest, In Motion, During Processing
  • Building Infrastructure to Implement Security Strategies

Jesse Tetreault             Dejan Kocic
Jesse Tetreault
Solutions Architect at Nvidia
            Dejan Kocic
AI Specialist at NetApp

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