Muhammad Binsawad*
CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3645-3663, 2024, DOI:10.32604/cmc.2024.048183
Abstract Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity, and because of its complexity and evasiveness, it is challenging to identify using traditional signature-based detection approaches. The study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses, highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial methodologies. The article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model Tree. Using a dataset from the Canadian Institute for Cybersecurity, a comparative analysis is carried out with well-known machine learning… More >
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