2 citations · 3 across the 7 of their papers we have counts for
7 papers
LLM-Assisted Web Measurements
Simone Bozzolan, Stefano Calzavara, Lorenzo Cazzaro
Web measurements are a well-established methodology for assessing the security and privacy landscape of the Internet. However, existing top lists of popular websites are unlabeled…
Watermarking Decision Tree Ensembles
Stefano Calzavara, Lorenzo Cazzaro, Donald Gera +1
Protecting the intellectual property of machine learning models is a hot topic and many watermarking schemes for deep neural networks have been proposed in the literature. Unfortun…
Timber! Poisoning Decision Trees
Stefano Calzavara, Lorenzo Cazzaro, Massimo Vettori
We present Timber, the first white-box poisoning attack targeting decision trees. Timber is based on a greedy attack strategy that leverages sub-tree retraining to efficiently esti…
Verifiable Boosted Tree Ensembles
Stefano Calzavara, Lorenzo Cazzaro, Claudio Lucchese +1
Verifiable learning advocates for training machine learning models amenable to efficient security verification. Prior research demonstrated that specific classes of decision tree e…
Verifiable Learning for Robust Tree Ensembles
Stefano Calzavara, Lorenzo Cazzaro, Giulio Ermanno Pibiri +1
Verifying the robustness of machine learning models against evasion attacks at test time is an important research problem. Unfortunately, prior work established that this problem i…
Explainable Global Fairness Verification of Tree-Based Classifiers
Stefano Calzavara, Lorenzo Cazzaro, Claudio Lucchese +1
We present a new approach to the global fairness verification of tree-based classifiers. Given a tree-based classifier and a set of sensitive features potentially leading to discri…
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
Stefano Calzavara, Lorenzo Cazzaro, Claudio Lucchese +2
In this paper we criticize the robustness measure traditionally employed to assess the performance of machine learning models deployed in adversarial settings. To mitigate the limi…