26 citations · 95 across the 12 of their papers we have counts for
6 papers · 1 filter
Deep Defence on Wheels: A Dual Intrusion Detection System Architecture for Comprehensive In-Vehicle Network Security
Shashwat Khandelwal, Shanker Shreejith
Increasing connectivity to the outside world and the lack of inbuilt security mechanisms have made legacy intra-vehicular networks vulnerable to cyberattacks. Initial research focu…
Quantised Neural Network Accelerators for Low-Power IDS in Automotive Networks
Shashwat Khandelwal, Anneliese Walsh, Shanker Shreejith
In this paper, we explore low-power custom quantised Multi-Layer Perceptrons (MLPs) as an Intrusion Detection System (IDS) for automotive controller area network (CAN). We utilise…
Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN
Shashwat Khandelwal, Shreejith Shanker
Vehicles today comprise intelligent systems like connected autonomous driving and advanced driving assistance systems (ADAS) to enhance the driving experience, which is enabled thr…
Real-Time Zero-Day Intrusion Detection System for Automotive Controller Area Network on FPGAs
Shashwat Khandelwal, Shreejith Shanker
Increasing automation in vehicles enabled by increased connectivity to the outside world has exposed vulnerabilities in previously siloed automotive networks like controller area n…
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs
Shashwat Khandelwal, Shreejith Shanker
Rising connectivity in vehicles is enabling new capabilities like connected autonomous driving and advanced driver assistance systems (ADAS) for improving the safety and reliabilit…
Deep Learning-based Embedded Intrusion Detection System for Automotive CAN
Shashwat Khandelwal, Eashan Wadhwa, Shreejith Shanker
Rising complexity of in-vehicle electronics is enabling new capabilities like autonomous driving and active safety. However, rising automation also increases risk of security threa…