3 citations · 3 across the 2 of their papers we have counts for
3 papers · 1 filter
Privacy-Preserving GNN Inference on Financial Transaction Graphs via Homomorphic Encryption
H. Çağrı Bilgi, Kemal Mutluergil, Ceren Yıldırım +2
Anti-money laundering (AML) in financial networks requires modeling transaction patterns that span multiple institutions. In practice, however, banks cannot share account and trans…
Combining Homomorphic Encryption and Differential Privacy in Federated Learning for Model Inspection and Availability
Ceren Yıldırım, Kamer Kaya, Sinan Yıldırım +1
The increasing prevalence of decentralized data has led to a growing interest in federated learning, which enables collaborative model training without clients sharing their sensit…
ML with HE: Privacy Preserving Machine Learning Inferences for Genome Studies
Ş. S. Mağara, C. Yıldırım, F. Yaman +6
Preserving the privacy and security of big data in the context of cloud computing, while maintaining a certain level of efficiency of its processing remains to be a subject, open f…