👉 Attack computing is an emerging field that focuses on the development of computing systems and techniques designed to be resilient against adversarial attacks, where malicious actors attempt to manipulate or deceive these systems into making incorrect decisions. This includes both data poisoning, where training data is corrupted to degrade model performance, and model extraction, where attackers steal the secrets of a trained model. Attack computing also encompasses adversarial training, where models are trained on adversarial examples to improve their robustness, and defensive mechanisms like input sanitization and anomaly detection. The goal is to create more secure and reliable AI systems that can withstand sophisticated attacks, ensuring trustworthiness in critical applications such as autonomous vehicles, healthcare, and financial services.
