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HomeHomework Helpcomputer-scienceThreat Modelling for AI

Threat Modelling for AI

The process of identifying, analyzing, and prioritizing potential threats to Agentic AI applications, as well as developing and implementing strategies to mitigate or counter these threats, including threat models, taxonomies, and playbooks

intermediate
3 hours
Computer Science
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Overview

Threat modelling and mitigation for agentic AI is a critical area of study that focuses on identifying and addressing potential risks associated with autonomous AI systems. As AI technology continues to advance, understanding how to model threats and implement effective mitigation strategies becomes...

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Key Terms

Agentic AI
AI systems that can act autonomously and make decisions.

Example: Self-driving cars are a form of agentic AI.

Threat Modelling
The process of identifying and evaluating potential threats to a system.

Example: Threat modelling helps in understanding risks in software development.

Vulnerability
A weakness in a system that can be exploited by threats.

Example: Software bugs can create vulnerabilities in applications.

Mitigation
Strategies or actions taken to reduce the impact of threats.

Example: Implementing firewalls is a common mitigation strategy.

Risk Assessment
The process of identifying and analyzing potential risks.

Example: Risk assessment is crucial in project management.

Autonomy
The ability of an AI to operate independently without human intervention.

Example: Robots in manufacturing often operate autonomously.

Related Topics

Cybersecurity Fundamentals
Understanding the basics of cybersecurity is crucial for protecting AI systems.
intermediate
Ethics in AI
Exploring the ethical implications of AI technologies and their societal impact.
intermediate
Risk Management Principles
Learning how to manage risks effectively in various contexts, including technology.
intermediate

Key Concepts

Agentic AIThreat ModellingMitigation StrategiesRisk Assessment