8 citations · 8 across the 3 of their papers we have counts for
3 papers
PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning
Harsh Kasyap, Anil Kumar Pradhan, Ugur Ilker Atmaca +2
Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing user privacy. However, traditiona…
Privacy-preserving Fuzzy Name Matching for Sharing Financial Intelligence
Harsh Kasyap, Ugur Ilker Atmaca, Carsten Maple +2
Financial institutions rely on data for many operations, including a need to drive efficiency, enhance services and prevent financial crime. Data sharing across an organisation or…
A privacy preserving querying mechanism with high utility for electric vehicles
Ugur Ilker Atmaca, Sayan Biswas, Carsten Maple +1
Electric vehicles (EVs) are gaining popularity due to the growing awareness for a sustainable future. However, since there are disproportionately fewer charging stations than EVs,…