26 citations · 95 across the 12 of their papers we have counts for
15 papers
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…
Context-aware Simopt-Power: Using structural data with simulation metadata to optimise FPGA designs
Eashan Wadhwa, Georgios Floros, Shanker Shreejith
Pre-implementation behavioural simulation routinely validates functional correctness, yet it also produces rich switching-activity traces that are typically discarded by FPGA compu…
An Empirical Study of Reducing AV1 Decoder Complexity and Energy Consumption via Encoder Parameter Tuning
Vibhoothi Vibhoothi, Julien Zouein, Shanker Shreejith +2
The widespread adoption of advanced video codecs such as AV1 is often hindered by their high decoding complexity, posing a challenge for battery-constrained devices. While encoders…
Simopt-Power: Leveraging Simulation Metadata for Low-Power Design Synthesis
Eashan Wadhwa, Shanker Shreejith
Excessive switching activity is a primary contributor to dynamic power dissipation in modern FPGAs, where fine-grained configurability amplifies signal toggling and associated capa…
SecCAN: An Extended CAN Controller with Embedded Intrusion Detection
Shashwat Khandelwal, Shreejith Shanker
Recent research has highlighted the vulnerability of in-vehicle network protocols such as controller area networks (CAN) and proposed machine learning-based intrusion detection sys…
An Energy-Efficient Artefact Detection Accelerator on FPGAs for Hyper-Spectral Satellite Imagery
Cornell Castelino, Shashwat Khandelwal, Shanker Shreejith +1
Hyper-Spectral Imaging (HSI) is a crucial technique for analysing remote sensing data acquired from Earth observation satellites. The rich spatial and spectral information obtained…
Simopt -- Simulation pass for Speculative Optimisation of FPGA-CAD flow
Eashan Wadhwa, Shanker Shreejith
Behavioural simulation is deployed in CAD flow to verify the functional correctness of a Register Transfer Level (RTL) design. Metadata extracted from behavioural simulation could…
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…
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…
DeCoRIC: Decentralized Connected Resilient IoT Clustering
Nitin Shivaraman, Saravanan Ramanathan, Shreejith Shanker +2
Maintaining peer-to-peer connectivity with low energy overhead is a key requirement for several emerging Internet of Things (IoT) applications. It is also desirable to develop such…