39 citations · 47 across the 4 of their papers we have counts for
6 papers
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.…
Topological safeguard for evasion attack interpreting the neural networks' behavior
Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Iñigo Mendialdua +1
In the last years, Deep Learning technology has been proposed in different fields, bringing many advances in each of them, but identifying new threats in these solutions regarding…
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…
Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment
Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Ines Goicoechea-Telleria +1
Deep Neural Networks were first developed decades ago, but it was not until recently that they started being extensively used, due to their computing power requirements. Since then…
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…
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…