A multimodal approach for windows malware detection using comprehensive analysis on called APIs

This academic paper presents a method for detecting Windows malware (malicious software) by analyzing multiple types of data together, specifically focusing on the API (application programming interface, the set of functions a program uses to interact with the operating system) calls that malware makes. The research uses a multimodal approach, meaning it combines different sources of information to improve detection accuracy.