Fabricio Ceschin

Orcid: 0000-0001-6853-8083

According to our database1, Fabricio Ceschin authored at least 17 papers between 2018 and 2024.

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Bibliography

2024
ANDROIDGYNY: Reviewing Clustering Techniques for Android Malware Family Classification.
DTRAP, 2024

Machine Learning (In) Security: A Stream of Problems.
DTRAP, 2024

2023
Fast & Furious: On the modelling of malware detection as an evolving data stream.
Expert Syst. Appl., 2023

People Still Care About Facts: Twitter Users Engage More with Factual Discourse than Misinformation.
Proceedings of the Security and Privacy in Social Networks and Big Data, 2023

2022
Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles.
IEEE Trans. Biom. Behav. Identity Sci., 2022

Fast & Furious: Modelling Malware Detection as Evolving Data Streams.
CoRR, 2022

AntiViruses under the microscope: A hands-on perspective.
Comput. Secur., 2022

2021
Understanding uses and misuses of similarity hashing functions for malware detection and family clustering in actual scenarios.
Digit. Investig., 2021

Computer Users Have Unique Yet Temporally Inconsistent Computer Usage Profiles.
CoRR, 2021

Challenges and pitfalls in malware research.
Comput. Secur., 2021

TeamUFPR at IDPT 2021: Equalizing a Strategy Using Machine Learning for Two Types of Data in Detecting Irony.
Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2021) co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2021), 2021

Taking a Peek: An Evaluation of Anomaly Detection Using System calls for Containers.
Proceedings of the IEEE Symposium on Computers and Communications, 2021

2020
Predicting Misinformation and Engagement in COVID-19 Twitter Discourse in the First Months of the Outbreak.
CoRR, 2020

We need to talk about antiviruses: challenges & pitfalls of AV evaluations.
Comput. Secur., 2020

2019
The AV says: Your Hardware Definitions Were Updated!
Proceedings of the 14th International Symposium on Reconfigurable Communication-centric Systems-on-Chip, 2019

L(a)ying in (Test)Bed - How Biased Datasets Produce Impractical Results for Actual Malware Families' Classification.
Proceedings of the Information Security - 22nd International Conference, 2019

2018
The Need for Speed: An Analysis of Brazilian Malware Classifers.
IEEE Secur. Priv., 2018


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