457 citations · 648 across the 21 of their papers we have counts for
22 papers
JASPER: Special Session on Joint Reliability And Security Assessment of SPlit Computing for Edge Robustness
Enrico Magliano, Giuseppe Esposito, Amir Hossein Shahdadian +13
Split Computing (SC) enables efficient deployment of Deep Neural Networks (DNNs) by partitioning inference between edge devices and cloud servers. However, intermediate feature rep…
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-…
SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks
Anil Bayram Gogebakan, Enrico Magliano, Alessio Carpegna +3
As artificial neural networks become increasingly integrated into safety-critical systems such as autonomous vehicles, devices for medical diagnosis, and industrial automation, ens…
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…
A Micro Architectural Events Aware Real-Time Embedded System Fault Injector
Enrico Magliano, Alessio Carpegna, Alessadro Savino +1
In contemporary times, the increasing complexity of the system poses significant challenges to the reliability, trustworthiness, and security of the SACRES. Key issues include the…
Design Space Exploration of Approximate Computing Techniques with a Reinforcement Learning Approach
Sepide Saeedi, Alessandro Savino, Stefano Di Carlo
Approximate Computing (AxC) techniques have become increasingly popular in trading off accuracy for performance gains in various applications. Selecting the best AxC techniques for…
Security layers and related services within the Horizon Europe NEUROPULS project
Fabio Pavanello, Cedric Marchand, Paul Jimenez +17
In the contemporary security landscape, the incorporation of photonics has emerged as a transformative force, unlocking a spectrum of possibilities to enhance the resilience and ef…
PSP Framework: A novel risk assessment method in compliance with ISO/SAE-21434
Franco Oberti, Ernesto Sanchez, Alessandro Savino +2
As more cars connect to the internet and other devices, the automotive market has become a lucrative target for cyberattacks. This has made the industry more vulnerable to security…
NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS
Fabio Pavanello, Cedric Marchand, Ian O'Connor +34
This special session paper introduces the Horizon Europe NEUROPULS project, which targets the development of secure and energy-efficient RISC-V interfaced neuromorphic accelerators…
Validation, Verification, and Testing (VVT) of future RISC-V powered cloud infrastructures: the Vitamin-V Horizon Europe Project perspective
Marti Alonso, David Andreu, Ramon Canal +10
Vitamin-V is a project funded under the Horizon Europe program for the period 2023-2025. The project aims to create a complete open-source software stack for RISC-V that can be use…
Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies
Fabio Pavanello, Elena Ioana Vatajelu, Alberto Bosio +6
The field of neuromorphic computing has been rapidly evolving in recent years, with an increasing focus on hardware design and reliability. This special session paper provides an o…
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-…
Fast Exploration of the Impact of Precision Reduction on Spiking Neural Networks
Sepide Saeedi, Alessio Carpegna, Alessandro Savino +1
Approximate Computing (AxC) techniques trade off the computation accuracy for performance, energy, and area reduction gains. The trade-off is particularly convenient when the appli…
Micro-Architectural features as soft-error induced fault executions markers in embedded safety-critical systems: a preliminary study
Deniz Kasap, Alessio Carpegna, Alessandro Savino +1
Radiation-induced soft errors are one of the most challenging issues in Safety Critical Real-Time Embedded System (SACRES) reliability, usually handled using different flavors of D…
LIN-MM: Multiplexed Message Authentication Code for Local Interconnect Network message authentication in road vehicles
Franco Oberti, Ernesto Sanchez, Alessandro Savino +3
The automotive market is profitable for cyberattacks with the constant shift toward interconnected vehicles. Electronic Control Units (ECUs) installed on cars often operate in a cr…
CAN-MM: Multiplexed Message Authentication Code for Controller Area Network message authentication in road vehicles
Franco Oberti, Ernesto Sanchez, Alessandro Savino +2
The automotive market is increasingly profitable for cyberattacks with the constant shift toward fully interconnected vehicles. Electronic Control Units (ECUs) installed on cars of…
Using analog scrambling circuits for automotive sensor integrity and authenticity
Cristiano Pegoraro Chenet, Alessandro Savino, Stefano di Carlo
The automotive domain rapidly increases the embedded amount of complex and interconnected electronics systems. A considerable proportion of them are real-time safety-critical devic…
Spiker: an FPGA-optimized Hardware acceleration for Spiking Neural Networks
Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
Spiking Neural Networks (SNN) are an emerging type of biologically plausible and efficient Artificial Neural Network (ANN). This work presents the development of a hardware acceler…
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…
Securing Soft IP Cores in FPGA based Reconfigurable Mobile Heterogeneous Systems
Alberto Carelli, Cataldo Basile, Alessandro Savino +2
The mobile application market is rapidly growing and changing, offering always brand new software to install in increasingly powerful devices. Mobile devices become pervasive and m…
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…