Machine learning (ML) plays a crucial role in cybersecurity by analyzing large and complex datasets from threat logs, enabling faster identification of cyberthreats. Kaspersky utilizes ML algorithms to detect anomalies and enhance malware identification. By processing data from Kaspersky Security Network, ML tools like Random Forest algorithm help predict and identify new threats
ML's continuous learning ensures robust defense by reconstructing cyber-reality from logs, offering insights into security posture. Challenges include dataset preparation, implementation, and model interpretability. ML models have identified thousands of new threats, emphasizing the importance of leveraging ML in cybersecurity to stay ahead of evolving threats. Future directions include deep learning and reinforcement learning to improve threat detection capabilities and developing robust and scalable solutions in cybersecurity. ```https://securelist.com/machine-learning-in-threat-hunting/114016/