Fabrício Ceschin
Fabrício Ceschin
Postdoctoral Researcher at Georgia Tech
Verified email at - Homepage
Cited by
Cited by
The Need for Speed: An Analysis of Brazilian Malware Classifers
F Ceschin, F Pinage, M Castilho, D Menotti, LS Oliveira, A Gregio
IEEE Security & Privacy 16 (6), 31-41, 2018
Shallow Security: on the Creation of Adversarial Variants to Evade Machine Learning-Based Malware Detectors
F Ceschin, M Botacin, HM Gomes, LS Oliveira, A Grégio
We need to talk about antiviruses: challenges & pitfalls of av evaluations
M Botacin, F Ceschin, P De Geus, A Grégio
Computers & Security 95, 101859, 2020
Challenges and pitfalls in malware research
M Botacin, F Ceschin, R Sun, D Oliveira, A Grégio
Computers & Security 106, 102287, 2021
Predicting misinformation and engagement in COVID-19 Twitter discourse in the first months of the outbreak
M Silva, F Ceschin, P Shrestha, C Brant, J Fernandes, CS Silva, A Grégio, ...
arXiv preprint arXiv:2012.02164, 2020
Antiviruses under the microscope: A hands-on perspective
M Botacin, FD Domingues, F Ceschin, R Machnicki, MAZ Alves, ...
Computers & Security 112, 102500, 2022
L (a) ying in (Test) Bed: How Biased Datasets Produce Impractical Results for Actual Malware Families’ Classification
T Beppler, M Botacin, FJO Ceschin, LES Oliveira, A Grégio
Information Security: 22nd International Conference, ISC 2019, New York City …, 2019
Fast & Furious: On the modelling of malware detection as an evolving data stream
F Ceschin, M Botacin, HM Gomes, F Pinagé, LS Oliveira, A Grégio
Expert Systems with Applications 212, 118590, 2023
Machine learning (in) security: A stream of problems
F Ceschin, M Botacin, A Bifet, B Pfahringer, LS Oliveira, HM Gomes, ...
Digital Threats: Research and Practice, 2020
No need to teach new tricks to old malware: Winning an evasion challenge with xor-based adversarial samples
F Ceschin, M Botacin, G Lüders, HM Gomes, L Oliveira, A Gregio
Reversing and Offensive-oriented Trends Symposium, 13-22, 2020
The AV says: Your Hardware Definitions Were Updated!
M Botacin, L Galante, F Ceschin, PC Santos, L Carro, P de Geus, ...
ReCoSoC 2019, 2019
Understanding uses and misuses of similarity hashing functions for malware detection and family clustering in actual scenarios
M Botacin, VHG Moia, F Ceschin, MAA Henriques, A Grégio
Forensic Science International: Digital Investigation 38, 301220, 2021
Taking a peek: An evaluation of anomaly detection using system calls for containers
GR Castanhel, T Heinrich, F Ceschin, C Maziero
2021 IEEE Symposium on Computers and Communications (ISCC), 1-6, 2021
Detecçao de anomalias: Estudo de técnicas de identificaçao de ataques em um ambiente de contêiner
GR Castanhel, T Heinrich, F Ceschin, CA Maziero
Anais Estendidos do XX Simpósio Brasileiro em Segurança da Informação e de …, 2020
ANDROIDGYNY: Reviewing clustering techniques for Android malware family classification
TSR Pimenta, F Ceschin, A Gregio
Digital Threats: Research and Practice, 2023
Spotting the Differences: Quirks of Machine Learning (in) Security
F Ceschin
USENIX ENIGMA 2023, 2023
Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles
L Giovanini, F Ceschin, M Silva, A Chen, R Kulkarni, S Banda, M Lysaght, ...
IEEE Transactions on Biometrics, Behavior, and Identity Science 4 (3), 412-423, 2022
Corvus: Uma solução Sandbox e de Threat Intelligence para Identificação e Análise de Malware
M Botacin, F Ceschin, A Grégio
Anais Estendidos do XXI Simpósio Brasileiro em Segurança da Informação e de …, 2021
People Still Care About Facts: Twitter Users Engage More with Factual Discourse than Misinformation
L Giovanini, S Gilda, M Silva, F Ceschin, P Shrestha, C Brant, ...
International Symposium on Security and Privacy in Social Networks and Big …, 2023
Computer Users Have Unique Yet Temporally Inconsistent Computer Usage Profiles.
L Giovanini, F Ceschin, M Silva, A Chen, R Kulkarni, S Banda, M Lysaght, ...
CoRR, 2021
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