👉 Attacked computing, also known as adversarial attacks, refers to a class of security threats targeting machine learning models, particularly those used in artificial intelligence. These attacks involve manipulating input data to cause the model to make incorrect predictions or classifications, often by introducing subtle, imperceptible perturbations that are designed to fool the model. For instance, an attacker might add a tiny noise pattern to an image that is undetectable to humans but causes the AI system, such as a self-driving car's object-detection model, to misidentify a stop sign as a speed limit sign. This form of attack highlights vulnerabilities in AI systems and underscores the need for robust defenses to ensure the reliability and security of machine learning applications.
