The objective of this project is to build a malware detection system that analyzes API call sequences generated by programs during execution. By studying system-level interactions, the system detects malicious behavior patterns that indicate malware activity.
Study system APIs and how applications interact with operating systems.
Research malicious API call patterns used by malware.
Design a controlled environment to log API call sequences.
Extract sequential patterns from execution logs.
Implement feature engineering to convert API sequences into model-ready formats.
Apply classification algorithms to distinguish benign and malicious behaviors.
Evaluate temporal relationships between API calls.
Develop reporting features summarizing suspicious sequences.
Test the system using controlled malware execution samples.
Measure model accuracy and detection efficiency.
Document challenges in dynamic analysis environments.
