3 papers indexed
Abreu Quevedo, Roger Immich, Giancarlo Lucca, Graçaliz Dimuro, Bruno L. Dalmazo
This work investigates a generalized Choquet-integral-based feature aggregation framework to improve anomaly detection in high-dimensional network traffic data. The approach combines adaptive weighting with incremental feature selection to address feature redundancy. Using Random…
Iuri Mundstock, Abreu Quevedo, Jéferson Campos Nobre, Roben C. Lunardi, Thiago L. T. da Silveira, Bruno L. Dalmazo
Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistical features. In this work, we explore the use of entropy as an additional feature to support supervis…
Arthur G. Bubolz, Abreu Quevedo, Giancarlo Lucca, Rafael A. Berri, Eduardo Borges, Bruno L. Dalmazo
The growing use of Bitcoin as a decentralized digital asset and investment tool has sparked strong interest in understanding its market behavior. This study presents a new approach to analyze Bitcoin market sentiment by combining on-chain and financial data with social media post…