On-device Online Learning and Semantic Management of TinyML Systems
Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded devices for real-time on-device Machine Learning (ML). While many acknowledge the potential benefits of TinyML, its practical implementation presents unique challenges. This ...
Lightweight Hardware-Based Cache Side-Channel Attack Detection for Edge Devices (Edge-CaSCADe)
Cache Side-Channel Attacks (CSCAs) have been haunting most processor architectures for decades now. Existing approaches to mitigation of such attacks have certain drawbacks, namely software mishandling, performance overhead, and low throughput due to ...
Coupling bit and modular arithmetic for efficient general-purpose fully homomorphic encryption
Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data. This property is desirable for outsourced computation of sensitive data as it relies solely on the underlying security of the cryptosystem and not in access control ...
A Review of Abstraction Methods Toward Verifying Neural Networks
Neural networks as a machine learning technique are increasingly deployed in various domains. Despite their performance and their continuous improvement, the deployment of neural networks in safety-critical systems, in particular for autonomous mobility, ...
Elements of Timed Pattern Matching
The rise of machine learning and cloud technologies has led to a remarkable influx of data within modern cyber-physical systems. However, extracting meaningful information from this data has become a significant challenge due to its volume and complexity. ...
