396 citations · 601 across the 20 of their papers we have counts for
20 papers
Federated Split Learning with Only Positive Labels for resource-constrained IoT environment
Praveen Joshi, Chandra Thapa, Mohammed Hasanuzzaman +2
Distributed collaborative machine learning (DCML) is a promising method in the Internet of Things (IoT) domain for training deep learning models, as data is distributed across mult…
ACE: A Consent-Embedded privacy-preserving search on genomic database
Sara Jafarbeiki, Amin Sakzad, Ron Steinfeld +3
In this paper, we introduce ACE, a consent-embedded searchable encryption scheme. ACE enables dynamic consent management by supporting the physical deletion of associated data at t…
Discretization-based ensemble model for robust learning in IoT
Anahita Namvar, Chandra Thapa, Salil S. Kanhere
IoT device identification is the process of recognizing and verifying connected IoT devices to the network. This is an essential process for ensuring that only authorized devices c…
Access-based Lightweight Physical Layer Authentication for the Internet of Things Devices
Saud Khan, Chandra Thapa, Salman Durrani +1
Physical-layer authentication is a popular alternative to the conventional key-based authentication for internet of things (IoT) devices due to their limited computational capacity…
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Qun Li, Chandra Thapa, Lawrence Ong +5
Federated learning (FL) is the most popular distributed machine learning technique. FL allows machine-learning models to be trained without acquiring raw data to a single point for…
Enabling All In-Edge Deep Learning: A Literature Review
Praveen Joshi, Mohammed Hasanuzzaman, Chandra Thapa +2
In recent years, deep learning (DL) models have demonstrated remarkable achievements on non-trivial tasks such as speech recognition and natural language understanding. One of the…