How does Predictive Machine Learning enhance malware protection?

Predictive Machine Learning enhances malware protection significantly by identifying previously unknown threats through file analysis. This approach utilizes algorithms trained on large datasets to recognize patterns and behaviors typically associated with malicious software, even if those specific threats have not been previously documented or identified. This proactive capability allows for the detection of new and evolving malware strains that traditional signature-based methods might miss.

By analyzing the characteristics and behaviors of files, Machine Learning models can assess the likelihood of a file being malicious based on similarities to known threats or by applying heuristics that indicate malicious intent. This adaptability to emerging threats is essential as cyber threats become more sophisticated, ensuring a higher level of security for systems that rely on this technology.

The other options focus on static methods like scanning for known threats or limiting actions taken on files, which do not allow for dynamic identification of newer, unpredictable threats.