About this document

(L) KiML 2023 Paper 1 Highlighted by mohnishkrishna1225 is a document available to read on EtoBox.

This research proposes a concise feature set of just 12 PDF-specific features for malware detection, achieving a high accuracy of 99.75% using a Random Forest model. The study emphasizes the importance of using features that require minimal domain knowledge, contrasting with existing methods that rely on larger, more complex feature sets. By focusing on static features unique to PDF files, the proposed approach aims to enhance detection efficiency while reducing the risk of overfitting.

Author

mohnishkrishna1225

Language

EN