Google's AI Red Team - PowerPoint PPT Presentation

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Google's AI Red Team

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Updated: 27 September 2023
Slides: 8
Provided by: infosectrain02
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Title: Google's AI Red Team


1
GOOGLE'S
learntorise
AI RED TEAM
ADVANCING CYBERSECURITY
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2
WHAT IS GOOGLE'S AI RED TEAM?
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learntorise
Google's AI Red Team is a specialized cybersecurit
y team that secures AI-driven technologies. They
possess expertise in attacking machine learning
systems and collaborate with AI experts to
identify and resolve vulnerabilities. Their goal
is to proactively safeguard Google's AI
deployments and stay ahead of potential threats.
3
COMMON ATTACKS ON AI
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01 Adversarial Attacks on AI Systems
02 Data Poisoning AI
03 Prompt Injection Attacks
04 Backdoor Attacks on AI Models
4
HOW GOOGLE'S AI RED TEAM ADDRESSING
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AI ATTACKS?
Inspired by military tactics, Google's AI Red
Team mimics adversaries to uncover AI system
vulnerabilities. While traditional red teams
offer a foundation, AI attacks demand
specialized expertise. With deep AI expertise,
Google's AI Red Team empowers defenders by
proactively identifying vulnerabilities
enhancing AI system security from the start.
5
KEY FEATURES OF
GOOGLE AI RED TEAM
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  • Google established a dedicated AI Red Team to
    address the unique challenges of machine
  • learning systems' security vulnerabilities.
  • Unlike traditional red teams, the AI Red Team
    possesses a specialized skill set in attacking ML
  • systems, requiring a deep understanding of
    machine learning technology.
  • The teams are closely aligned, collaborating on
    exercises that combine classic security attack
  • vectors with new ML-specific tactics.

6
04 The AI Red Team strategically targets AI
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  • deployments by setting up scenarios based on
  • threat intelligence and theoretical attacks,
    executing multiple steps to achieve realistic
    adversarial simulations.
  • Collaboration between the red team and AI
    experts enables access to specific internal
  • positions for targeting ML models effectively.
  • The AI Red Team's engaging attack narratives
    help drive visibility and investment in ML
    safety,
  • emphasizing the importance of securing AI-driven
    technologies.

7
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