Adversarialhyökkäyksiä
Adversarialhyökkäyksiä, or adversarial attacks, are techniques used to manipulate machine learning models into making incorrect predictions. These attacks exploit vulnerabilities in the model's learning process or its underlying architecture. The goal is to introduce small, often imperceptible changes to input data that cause the model to misclassify the input.
These attacks can be categorized based on the attacker's knowledge of the model. White-box attacks assume the
Adversarial attacks pose a significant threat to the security and reliability of AI systems. For instance,
Researchers are actively developing defenses against adversarial attacks. These include adversarial training, where models are trained