activity
20192024
most citedCascading Machine Learning to Attack Bitcoin Anonymity

39 citations · 45 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CR2024

Unveiling Dynamics and Patterns: A Comprehensive Analysis of Spreading Patterns and Similarities in Low-Labelled Ransomware Families

Francesco Zola, Mikel Gorricho, Jon Ander Medina +2

Ransomware has become one of the most widespread threats, primarily due to its easy deployment and the accessibility to services that enable attackers to raise and obfuscate funds.…

cs.LG2024★ 1 cited

Enhancing Law Enforcement Training: A Gamified Approach to Detecting Terrorism Financing

Francesco Zola, Lander Segurola, Erin King +2

Tools for fighting cyber-criminal activities using new technologies are promoted and deployed every day. However, too often, they are unnecessarily complex and hard to use, requiri…

cs.LG2024

NeuralSentinel: Safeguarding Neural Network Reliability and Trustworthiness

Xabier Echeberria-Barrio, Mikel Gorricho, Selene Valencia +1

The usage of Artificial Intelligence (AI) systems has increased exponentially, thanks to their ability to reduce the amount of data to be analyzed, the user efforts and preserving…

cs.CR2022★ 1 cited

Conditional Generative Adversarial Network for keystroke presentation attack

Idoia Eizaguirre-Peral, Lander Segurola-Gil, Francesco Zola

Cybersecurity is a crucial step in data protection to ensure user security and personal data privacy. In this sense, many companies have started to control and restrict access to t…

cs.CV2022

Verification system based on long-range iris and Graph Siamese Neural Networks

Francesco Zola, Jose Alvaro Fernandez-Carrasco, Jan Lukas Bruse +2

Biometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision…

cs.LG2021

NBcoded: network attack classifiers based on Encoder and Naive Bayes model for resource limited devices

Lander Segurola-Gil, Francesco Zola, Xabier Echeberria-Barrio +1

In the recent years, cybersecurity has gained high relevance, converting the detection of attacks or intrusions into a key task. In fact, a small breach in a system, application, o…

cs.LG2021★ 2 cited

Temporal graph-based approach for behavioural entity classification

Francesco Zola, Lander Segurola, Jan Lukas Bruse +1

Graph-based analyses have gained a lot of relevance in the past years due to their high potential in describing complex systems by detailing the actors involved, their relations an…

cs.LG2020

Generative Adversarial Networks for Bitcoin Data Augmentation

Francesco Zola, Jan Lukas Bruse, Xabier Etxeberria Barrio +2

In Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these grou…

cs.PF2019★ 2 cited

Kriptosare.gen, a dockerized Bitcoin testbed: analysis of server performance

Francesco Zola, Cristina Pérez-Solá, Jon Egaña Zubia +2

Bitcoin is a peer-to-peer distributed cryptocurrency system, that keeps all transaction history in a public ledger known as blockchain. The Bitcoin network is implicitly pseudoanon…

cs.CR2019★ 39 cited

Cascading Machine Learning to Attack Bitcoin Anonymity

Francesco Zola, Maria Eguimendia, Jan Lukas Bruse +1

Bitcoin is a decentralized, pseudonymous cryptocurrency that is one of the most used digital assets to date. Its unregulated nature and inherent anonymity of users have led to a dr…