6 papers
Continual Backdoor Training in IoT/CPS
Oxana Salish, Kuniyilh S
Internet of Things (IoT) and Cyber-physical systems (CPS) increasingly rely on continual learning (CL) to adapt to evolving environments, device heterogeneity, and concept drift, t…
Backdoor Attacks on Fault Detection and Localization in Cyber-Physical Systems
Abile Jean, Kuniyilh S
Cyber-Physical Systems (CPS) integrate sensing, communication, computation, and control to support critical infrastructure, including smart grids, industrial automation, and contro…
CFD-HAR: User-controllable Privacy through Conditional Feature Disentanglement
Alex Gn, Fan Li, S Kuniyilh +1
Modern wearable and mobile devices are equipped with inertial measurement units (IMUs). Human Activity Recognition (HAR) applications running on such devices use machine-learning-b…
Backdoor Attacks on Contrastive Continual Learning for IoT Systems
Alfous Tim, Kuniyilh Simi D
The Internet of Things (IoT) systems increasingly depend on continual learning to adapt to non-stationary environments. These environments can include factors such as sensor drift,…
Contrastive Learning for Privacy Enhancements in Industrial Internet of Things
Lin Liu, Rita Machacy, Simi Kuniyilh
The Industrial Internet of Things (IIoT) integrates intelligent sensing, communication, and analytics into industrial environments, including manufacturing, energy, and critical in…
Backdoor Attacks on Multi-modal Contrastive Learning
Simi D Kuniyilh, Rita Machacy
Contrastive learning has become a leading self- supervised approach to representation learning across domains, including vision, multimodal settings, graphs, and federated learning…