By Associate Professor Gustavo Batista

Preprints

Hamza A; Gharakheili HH; Benson TA; Batista G; Sivaraman V, 2023, Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity, http://dx.doi.org/10.48550/arxiv.2304.04987

Pashamokhtari A; Okui N; Nakahara M; Kubota A; Batista G; Gharakheili HH, 2023, Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks, http://dx.doi.org/10.48550/arxiv.2301.06695

Pashamokhtari A; Batista G; Gharakheili HH, 2022, AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models against Adversarial Volumetric Attacks on IoT Networks, http://dx.doi.org/10.48550/arxiv.2203.09792

da Silva LT; Souza VMA; Batista GEAPA, 2021, An Open-Source Tool for Classification Models in Resource-Constrained Hardware, http://dx.doi.org/10.48550/arxiv.2105.05983

Souza VMA; Reis DMD; Maletzke AG; Batista GEAPA, 2020, Challenges in Benchmarking Stream Learning Algorithms with Real-world Data, http://dx.doi.org/10.48550/arxiv.2005.00113

Reis DD; de Souto M; de Sousa E; Batista G, 2020, Quantifying With Only Positive Training Data, http://dx.doi.org/10.48550/arxiv.2004.10356

Chen Y; Why A; Batista G; Mafra-Neto A; Keogh E, 2014, Flying Insect Classification with Inexpensive Sensors, http://dx.doi.org/10.48550/arxiv.1403.2654

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