457 citations · 547 across the 21 of their papers we have counts for
21 papers
A benchmark suite of intracellular Boolean model variants and multiscale simulations for computational biology
Marco Masera, Riccardo Smeriglio, Roberta Bardini +2
We present PhysiBench, an open resource for developing and evaluating computational methods in systems biology including a benchmark suite of 612 executable intracellular Boolean r…
InjectV: Modeling Fault Injection Attacks in RISC-V Simulation Environment
Niccolò Lentini, Giorgio Fardo, Stefano Di Carlo +1
Fault Injection Attacks (FIAs) are a significant threat to hardware security, capable of compromising systems by inducing malicious faults in computation or storage. Evaluating res…
GAP: Geometric Anchor Pre-training for Data-Efficient Visuomotor Learning of Manipulation Tasks
Davide Buoso, Andrea Protopapa, Stefano Di Carlo +2
Learning visuomotor policies from scarce expert demonstrations remains a core challenge in robotic manipulation. A primary hurdle lies in distilling high-dimensional RGB representa…
NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
Alessio Caviglia, Filippo Marostica, Roberta Bardini +2
The rapid expansion of spiking neural networks (SNNs) has led to a proliferation of training algorithms that differ widely in biological inspiration, computational structure, and h…
Elastic Spiking Transformers for Efficient Gesture Understanding
Alberto Ancilotto, Gianluca Amprimo, Stefano Di Carlo +1
Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applications. Yet current architectur…
Experimental Analysis of FreeRTOS Dependability through Targeted Fault Injection Campaigns
Luca Mannella, Stefano Di Carlo, Alessandro Savino
Real-Time Operating Systems (RTOSes) play a crucial role in safety-critical domains, where deterministic and predictable task execution is essential. Yet they are increasingly expo…
LuxIA: A Lightweight Unitary matriX-based Framework Built on an Iterative Algorithm for Photonic Neural Network Training
Tzamn Melendez Carmona, Federico Marchesin, Marco P. Abrate +3
PNNs present promising opportunities for accelerating machine learning by leveraging the unique benefits of photonic circuits. However, current state of the art PNN simulation tool…
Uncovering Privacy Vulnerabilities through Analytical Gradient Inversion Attacks
Tamer Ahmed Eltaras, Qutaibah Malluhi, Alessandro Savino +2
Federated learning has emerged as a prominent privacy-preserving technique for leveraging large-scale distributed datasets by sharing gradients instead of raw data. However, recent…
Neuromorphic Heart Rate Monitors: Neural State Machines for Monotonic Change Detection
Alessio Carpegna, Chiara De Luca, Federico Emanuele Pozzi +4
Detecting monotonic changes in heart rate (HR) is crucial for early identification of cardiac conditions and health management. This is particularly important for dementia patients…
Can social media shape the security of next-generation connected vehicles?
Nicola Scarano, Luca Mannella, Alessandro Savino +1
The increasing adoption of connectivity and electronic components in vehicles makes these systems valuable targets for attackers. While automotive vendors prioritize safety, there…
Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks
Alberto Dequino, Alessio Carpegna, Davide Nadalini +4
Rehearsal-based Continual Learning (CL) has been intensely investigated in Deep Neural Networks (DNNs). However, its application in Spiking Neural Networks (SNNs) has not been expl…
Navigating the road to automotive cybersecurity compliance
Franco Oberti, Fabrizio Abrate, Alessandro Savino +2
The automotive industry has evolved significantly since the introduction of the Ford Model T in 1908. Today's vehicles are not merely mechanical constructs; they are integral compo…
Vitamin-V: Expanding Open-Source RISC-V Cloud Environments
Ramon Canal, Stefano Di Carlo, Dimitris Gizopoulos +12
Among the key contributions of Vitamin-V (2023-2025 Horizon Europe project), we develop a complete RISC-V open-source software stack for cloud services with comparable performance…
CARACAS: vehiCular ArchitectuRe for detAiled Can Attacks Simulation
Sadek Misto Kirdi, Nicola Scarano, Franco Oberti +3
Modern vehicles are increasingly vulnerable to attacks that exploit network infrastructures, particularly the Controller Area Network (CAN) networks. To effectively counter such th…
R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional Gradients
Tamer Ahmed Eltaras, Qutaibah Malluhi, Alessandro Savino +3
In the effort to learn from extensive collections of distributed data, federated learning has emerged as a promising approach for preserving privacy by using a gradient-sharing mec…
SpikeExplorer: hardware-oriented Design Space Exploration for Spiking Neural Networks on FPGA
Dario Padovano, Alessio Carpegna, Alessandro Savino +1
One of today's main concerns is to bring Artificial Intelligence power to embedded systems for edge applications. The hardware resources and power consumption required by state-of-…
Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge
Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
Including Artificial Neural Networks in embedded systems at the edge allows applications to exploit Artificial Intelligence capabilities directly within devices operating at the ne…
Vitamin-V: Virtual Environment and Tool-boxing for Trustworthy Development of RISC-V based Cloud Services
A. Arelakis, J. M. Arnau, J. L. Berral +20
Vitamin-V is a 2023-2025 Horizon Europe project that aims to develop a complete RISC-V open-source software stack for cloud services with comparable performance to the cloud-domina…
A survey on hardware-based malware detection approaches
Cristiano Pegoraro Chenet, Alessandro Savino, Stefano Di Carlo
This paper delves into the dynamic landscape of computer security, where malware poses a paramount threat. Our focus is a riveting exploration of the recent and promising hardware-…
EXT-TAURUM P2T: an Extended Secure CAN-FD Architecture for Road Vehicles
Franco Oberti, Alessandro Savino, Ernesto Sanchez +2
The automobile industry is no longer relying on pure mechanical systems; instead, it benefits from advanced Electronic Control Units (ECUs) in order to provide new and complex func…
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark +144
Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations i…