Tag: adversarial attacks
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PoiCGAN: Targeted Poisoning Attack in Federated Learning
Discover PoiCGAN, a novel targeted poisoning attack using feature-label perturbation in federated learning, achieving high success with minimal accuracy lo...
Effective Strategies to Mitigate Many-Shot Jailbreaking in LLMs
Discover proven methods like fine-tuning and input sanitization to prevent many-shot jailbreaking attacks on large language models, enhancing AI safety.
Defending Neural Network Policies from Adversarial Attacks
Explore effective strategies to protect neural network policies from adversarial attacks threatening AI security in critical applications.
Defending Machine Learning Against Adversarial Attacks
Learn how adversarial examples threaten machine learning models and explore strategies to protect AI systems from deceptive attacks.
Transfer of Adversarial Robustness Across Perturbation Types
Explore how adversarial robustness transfers between perturbation types to enhance AI model resilience and improve training strategies.