Browsing School of Engineering by Subject "Quantised Neural Nets"
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Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN
(2023)Vehicles today comprise intelligent systems like connected autonomous driving and advanced driving assistance systems (ADAS) to enhance the driving experience, which is enabled through increased connectivity to ... -
Real-time zero-day Intrusion Detection System for Automotive Controller Area Network on FPGAs
(2023)Increasing automation in vehicles enabled by in- creased connectivity to the outside world has exposed vulnerabilities in previously siloed automotive networks like controller area networks (CAN). Attributes of CAN such ...