Resilience in machine learning refers to the ability of a system to remain effective and reliable, especially in the face of challenges. This quality is crucial in cybersecurity, where robust systems can better withstand attacks and adapt to evolving threats. Understanding and implementing resilience can significantly enhance the security posture of machine learning applications.
