7 citations · 17 across the 11 of their papers we have counts for
5 papers · 1 filter
DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation
Charuka Herath, Yogachandran Rahulamathavan, Varuna De Silva +1
Federated Learning (FL) enables decentralized model training without sharing raw data, offering strong privacy guarantees. However, existing FL protocols struggle to defend against…
Deep Learning for Encrypted Traffic Classification and Unknown Data Detection
Madushi H. Pathmaperuma, Yogachandran Rahulamathavan, Safak Dogan +2
Despite the widespread use of encryption techniques to provide confidentiality over Internet communications, mobile device users are still susceptible to privacy and security risks…
Privacy-preserving Similarity Calculation of Speaker Features Using Fully Homomorphic Encryption
Yogachandran Rahulamathavan
Recent advances in machine learning techniques are enabling Automated Speech Recognition (ASR) more accurate and practical. The evidence of this can be seen in the rising number of…
Scalar Product Lattice Computation for Efficient Privacy-preserving Systems
Yogachandran Rahulamathavan, Safak Dogan, Xiyu Shi +3
Privacy-preserving applications allow users to perform on-line daily actions without leaking sensitive information. Privacy-preserving scalar product is one of the critical algorit…
User Collusion Avoidance Scheme for Privacy-Preserving Decentralized Key-Policy Attribute-Based Encryption -- Full Version
Yogachandran Rahulamathavan
Recent trend towards cloud computing paradigm, smart devices and 4G wireless technologies has enabled seamless data sharing among users. Cloud computing environment is distributed…