4 papers
Low-Latency Spatial-Provenance Recovery Methods for Privacy-Constrained Vehicular Networks
Manish Bansal, J. Harshan
In multihop Vehicle-to-Everything (V2X) networks, Road Side Units (RSUs) intend to collect information on vehicles' location in a low-latency manner while respecting their privacy…
On Scaling LT-Coded Blockchains in Heterogeneous Networks and their Vulnerabilities to DoS Threats
Harikrishnan K., J. Harshan, Anwitaman Datta
Coded blockchains have acquired prominence as a promising solution to reduce storage costs and facilitate scalability. Within this class, Luby Transform (LT) coded blockchains are…
On Spatial-Provenance Recovery in Wireless Networks with Relaxed-Privacy Constraints
Manish Bansal, Pramsu Shrivastava, J. Harshan
In Vehicle-to-Everything (V2X) networks with multi-hop communication, Road Side Units (RSUs) intend to gather location data from the vehicles to offer various location-based servic…
On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning
Arpit Guleria, J. Harshan, Ranjitha Prasad +1
Class imbalance in training datasets can lead to bias and poor generalization in machine learning models. While pre-processing of training datasets can efficiently address both the…