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Publicação
Artificial Intelligence Models to Predict Malicious Network Traffic
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Orientador(es)
Resumo(s)
This research explores how Artificial Intelligence models can predict malicious network traffic.
This is relevant with the increasing number of cyberattacks, considering Artificial Intelligence
technology has the ability to protect against them. To do so, it is important to first determine
which models have are able to play this defensive role. The focus and objective of this research
is to understand the practical use and the predictive power of these models and, with the
power of Python, an experiment is conducted to assess whether there is a model that is able
to predict malicious network according to several metrics such as accuracy, support, recall,
and F1 score considering a public dataset found on Kaggle. The research proves that Artificial
Intelligence, and especially Machine Learning models, have the potential to help organizations
stay cybersafe against attacks, provided the models are used by professionals who are able to
understand not only the models, but also the business in which they are inserted.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Business Intelligence
Palavras-chave
Artificial Intelligence Cybersecurity Machine Learning Predictive Modelling SDG 9 - Industry, innovation and infrastructure