148 citations · 249 across the 20 of their papers we have counts for
9 papers · 1 filter
Pirates of Charity: Exploring Donation-based Abuses in Social Media Platforms
Bhupendra Acharya, Dario Lazzaro, Antonio Emanuele Cinà +1
With the widespread use of social media, organizations, and individuals use these platforms to raise funds and support causes. Unfortunately, this has led to the rise of scammers i…
Robust image classification with multi-modal large language models
Francesco Villani, Igor Maljkovic, Dario Lazzaro +3
Deep Neural Networks are vulnerable to adversarial examples, i.e., carefully crafted input samples that can cause models to make incorrect predictions with high confidence. To miti…
On the Robustness of Adversarial Training Against Uncertainty Attacks
Emanuele Ledda, Giovanni Scodeller, Daniele Angioni +5
In learning problems, the noise inherent to the task at hand hinders the possibility to infer without a certain degree of uncertainty. Quantifying this uncertainty, regardless of i…
Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms
Francesco Villani, Dario Lazzaro, Antonio Emanuele Cinà +3
Data poisoning attacks on clustering algorithms have received limited attention, with existing methods struggling to scale efficiently as dataset sizes and feature counts increase.…
Understanding XAI Through the Philosopher's Lens: A Historical Perspective
Martina Mattioli, Antonio Emanuele Cinà, Marcello Pelillo
Despite explainable AI (XAI) has recently become a hot topic and several different approaches have been developed, there is still a widespread belief that it lacks a convincing uni…
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Srishti Gupta, Zhang Chen, Luca Demetrio +9
Thanks to their extensive capacity, over-parameterized neural networks exhibit superior predictive capabilities and generalization. However, having a large parameter space is consi…
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor +5
Adversarial examples are typically optimized with gradient-based attacks. While novel attacks are continuously proposed, each is shown to outperform its predecessors using differen…
-zero: Gradient-based Optimization of -norm Adversarial Examples
Antonio Emanuele Cinà, Francesco Villani, Maura Pintor +3
Evaluating the adversarial robustness of deep networks to gradient-based attacks is challenging. While most attacks consider - and -norm constraints to craft i…
Conning the Crypto Conman: End-to-End Analysis of Cryptocurrency-based Technical Support Scams
Bhupendra Acharya, Muhammad Saad, Antonio Emanuele Cinà +5
The mainstream adoption of cryptocurrencies has led to a surge in wallet-related issues reported by ordinary users on social media platforms. In parallel, there is an increase in a…