4 Contributo in Atti di Convegno (Proceeding)

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4.1 Contributo in Atti di convegno 45414
4.2 Abstract in Atti di convegno 3514
4.3 Poster 846

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European Test Symposium Teams: an Anniversary Snapshot

The IEEE European Test Symposium (ETS) has been facilitating progress in electronic systems testing since its launch in 1996. On the occasion of its 30th anniversary, this collaborative paper gathers sections by 21 ETS teams to outline their influential ideas and milestones. Each team's section highlights historical perspective, current research, frameworks and projects as well as forward-looking research agendas in the area of electronic-based circuits and systems testing, reliability, safet...

Zero-Day Hardware-Supported Malware Detection of Stack Buffer Overflow Attacks: An Application Exploiting the CV32e40p RISC-V Core

The RISC-V architecture has become increasingly popular due to its open-source nature and flexibility, making it susceptible to various security attacks, such as Stack Buffer Overflow (SBO) attacks. It is crucial to effectively detect these attacks to ensure the security of RISC-V systems. This study explores Hardware-Supported Malware Detection (HMD) techniques for identifying these security threats. Using the CV32e40p RISC-V platform, we conducted simulations to assess the effectiveness of ...

Spike Train Scalograms (STS): a Deep Learning Classification Pipeline for Neuronal Cell Types

Classifying neuronal cell types is crucial for understanding the intricate circuitry of the cerebral cortex, which comprises diverse specialized neurons essential for brain function. Traditional Machine Learning (ML) approaches rely on manually engineered electrophysiological (EP) features, often overlooking subtle and complex patterns within spike train data. This study introduces a novel Spike Train Scalograms (STS)-based Deep Learning (DL) pipeline that integrates Continuous Wavelet Transf...

CANDoSA: A Hardware Performance Counter-Based Intrusion Detection System for DoS Attacks on Automotive CAN Bus

The Controller Area Network (CAN) protocol, essential for automotive embedded systems, lacks inherent security features, making it vulnerable to cyber threats, especially with the rise of autonomous vehicles. Traditional security measures offer limited protection, such as payload encryption and message authentication. This paper presents a novel Intrusion Detection System (IDS) designed for the CAN environment, utilizing Hardware Performance Counters (HPCs) to detect anomalies indicative of c...

Attributes Shape the Embedding Space of Face Recognition Models

Face Recognition (FR) tasks have made significant progress with the advent of Deep Neural Networks, particularly through margin-based triplet losses that embed facial images into high-dimensional feature spaces. During training, these contrastive losses focus exclusively on identity information as labels. However, we observe a multiscale geometric structure emerging in the embedding space, influenced by interpretable facial (e.g., hair color) and image attributes (e.g., contrast). We propose ...

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