26 citations · 95 across the 7 of their papers we have counts for
7 papers
Exploring Lightweight Federated Learning for Distributed Load Forecasting
Abhishek Duttagupta, Jin Zhao, Shanker Shreejith
Federated Learning (FL) is a distributed learning scheme that enables deep learning to be applied to sensitive data streams and applications in a privacy-preserving manner. This pa…
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…
A Lightweight FPGA-based IDS-ECU Architecture for Automotive CAN
Shashwat Khandelwal, Shreejith Shanker
Recent years have seen an exponential rise in complex software-driven functionality in vehicles, leading to a rising number of electronic control units (ECUs), network capabilities…
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…