Listar por autor "Zola, Francesco"
Mostrando ítems 1-7 de 7
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Attacking bitcoin anonymity: generative adversarial networks for improving bitcoin entity classification
Zola, Francesco; Segurola-Gil, Lander; Bruse, Jan Lukas; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (Springer, 2022) Artículo / ArtikuluaClassification of Bitcoin entities is an important task to help Law Enforcement Agencies reduce anonymity in the Bitcoin blockchain network and to detect classes more tied to illegal activities. However, this task is ... -
Behavioral analysis in cybersecurity using machine learning: a study based on graph representation, class imbalance and temporal dissection
The main goal of this thesis is to improve behavioral cybersecurity analysis using machine learning, exploiting graph structures, temporal dissection, and addressing imbalance problems.This main objective is divided into ... -
Bitcoin and cybersecurity: temporal dissection of blockchain data to unveil changes in entity behavioral patterns
Zola, Francesco; Bruse, Jan Lukas; Eguimendia, María; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (MDPI, 2019) Artículo / ArtikuluaThe Bitcoin network not only is vulnerable to cyber-attacks but currently represents the most frequently used cryptocurrency for concealing illicit activities. Typically, Bitcoin activity is monitored by decreasing anonymity ... -
Generative adversarial networks for bitcoin data augmentation
Zola, Francesco; Bruse, Jan Lukas; Etxeberria Barrio, Xabier; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (IEEE, 2020) Contribución a congreso / Biltzarrerako ekarpenaIn Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these ground-truth datasets are frequently affected ... -
Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing
Zola, Francesco; Segurola-Gil, L.; Bruse, Jan Lukas; Galar Idoate, Mikel ; Orduna Urrutia, Raúl (Elsevier, 2022) Artículo / ArtikuluaNetwork traffic analysis is an important cybersecurity task, which helps to classify anomalous, potentially dangerous connections. In many cases, it is critical not only to detect individual malicious connections, but to ... -
Temporal analysis of distribution shifts in malware classification for digital forensics
Zola, Francesco; Bruse, Jan Lukas; Galar Idoate, Mikel (IEEE, 2023) Contribución a congreso / Biltzarrerako ekarpenaIn recent years, malware diversity and complexity have increased substantially, so the detection and classification of malware families have become one of the key objectives of information security. Machine learning ... -
Verification system based on long-range iris and Graph Siamese Neural Networks
Zola, Francesco; Fernandez-Carrasco, José Álvaro; Bruse, Jan Lukas; Galar Idoate, Mikel ; Geradts, Zeno (ACM, 2022) Contribución a congreso / Biltzarrerako ekarpenaBiometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision. However, especially when physical ...