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Questions and Answers
What type of attacks involve manipulating input data to mislead AI/ML models?
Which type of attack specifically aims to evade detection by AI/ML-based security systems?
What type of attack introduces malicious data into training datasets used for ML models?
Which attack attempts to reverse-engineer or extract sensitive data from ML models?
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What type of attack involves the reverse-engineering and stealing of ML models?
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Study Notes
Types of Attacks on AI/ML Models
- Adversarial attacks: involve manipulating input data to mislead AI/ML models, which can lead to incorrect results or misclassification.
Evasion Attacks
- Specifically aim to evade detection by AI/ML-based security systems, allowing malicious data to go undetected.
Data Poisoning Attacks
- Introduce malicious data into training datasets used for ML models, causing the model to learn from incorrect or misleading data.
Model Inversion Attacks
- Attempt to reverse-engineer or extract sensitive data from ML models, potentially compromising confidential information.
Model Stealing Attacks
- Involve the reverse-engineering and stealing of ML models, allowing attackers to use or replicate the model for their own purposes.
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Description
Test your knowledge of increasing sophistication of attacks in Unit 4 with this quiz. Explore adversarial attacks and model evasion techniques used by attackers to manipulate AI/ML models and evade detection by security systems.
