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La-Casette / malicious_pdf_detection

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This project compares the performance of K-Nearest Neighbors, Support Vector Machines, and Decision Trees models for detecting malicious PDF files, with an emphasis on optimizing model performance and analyzing evasion techniques. It provides a comprehensive overview of machine learning for malicious PDF detection and potential vulnerabilities.

pdf machine-learning random-forest svm decision-trees knn malicious adversarial-learning pdf-malware evasion-attack
  • Updated Jan 22, 2023
  • Jupyter Notebook

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