3 citations · 3 across the 4 of their papers we have counts for
5 papers
Attacking Slicing Network via Side-channel Reinforcement Learning Attack
Wei Shao, Chandra Thapa, Rayne Holland +2
Network slicing in 5G and the future 6G networks will enable the creation of multiple virtualized networks on a shared physical infrastructure. This innovative approach enables the…
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…
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…