Predict Malware Using Machine Learning

• Main Author: Araújo, Domingos
• Publication Date: 2023
• Other Authors: Silva, Joaquim, Leite, Patrícia, Ribeiro, Óscar, Teixeira, Paulo
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/11110/3208
• topic: Machine learning; malvare; detection; artificial intelligence

This paper has as main goal to demonstrate how artificial intelligence models can be used to detect malicious files, executables, etc. The detection of malware allows preventing the loss of information, software, and hardware. Throughout this paper the models that were chosen and the results obtained by those models will be presented. The pipeline (application) that was created to help in the flow of information extraction, dataset creation, dataset processing, dataset training and testing for several models and the results will be presented. It will be shown how the pipeline helps in "fine-tuning" the models and datasets. It will be presented how the user can reproduce these results or obtain new results. In summary, the main objective of this paper is to demonstrate in a simple way which are the best Malware prediction models.