76 citations · 260 across the 32 of their papers we have counts for
8 papers · 1 filter
GOAT: GPU Outsourcing of Deep Learning Training With Asynchronous Probabilistic Integrity Verification Inside Trusted Execution Environment
Aref Asvadishirehjini, Murat Kantarcioglu, Bradley Malin
Machine learning models based on Deep Neural Networks (DNNs) are increasingly deployed in a wide range of applications ranging from self-driving cars to COVID-19 treatment discover…
Improving Accuracy of Federated Learning in Non-IID Settings
Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer
Federated Learning (FL) is a decentralized machine learning protocol that allows a set of participating agents to collaboratively train a model without sharing their data. This mak…
BlockFLA: Accountable Federated Learning via Hybrid Blockchain Architecture
Harsh Bimal Desai, Mustafa Safa Ozdayi, Murat Kantarcioglu
Federated Learning (FL) is a distributed, and decentralized machine learning protocol. By executing FL, a set of agents can jointly train a model without sharing their datasets wit…
How to Not Get Caught When You Launder Money on Blockchain?
Cuneyt G. Akcora, Sudhanva Purusotham, Yulia R. Gel +2
The number of blockchain users has tremendously grown in recent years. As an unintended consequence, e-crime transactions on blockchains has been on the rise. Consequently, public…
Secure IoT Data Analytics in Cloud via Intel SGX
Md Shihabul Islam, Mustafa Safa Ozdayi, Latifur Khan +1
The growing adoption of IoT devices in our daily life is engendering a data deluge, mostly private information that needs careful maintenance and secure storage system to ensure da…
Defending against Backdoors in Federated Learning with Robust Learning Rate
Mustafa Safa Ozdayi, Murat Kantarcioglu, Yulia R. Gel
Federated learning (FL) allows a set of agents to collaboratively train a model without sharing their potentially sensitive data. This makes FL suitable for privacy-preserving appl…