most citedBlockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things

160 citations · 349 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2023

A Survey on Congestion Control and Scheduling for Multipath TCP: Machine Learning vs Classical Approaches

Maisha Maliha, Golnaz Habibi, Mohammed Atiquzzaman

Multipath TCP (MPTCP) has been widely used as an efficient way for communication in many applications. Data centers, smartphones, and network operators use MPTCP to balance the tra…

cs.CR202333 cited

Smart Policy Control for Securing Federated Learning Management System

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammed Atiquzzaman

The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent healthcare systems, and various real-world applications have resulted in the generation of…

cs.CR202323 cited

Privacy-Preserving Ensemble Infused Enhanced Deep Neural Network Framework for Edge Cloud Convergence

Veronika Stephanie, Ibrahim Khalil, Mohammad Saidur Rahman +1

We propose a privacy-preserving ensemble infused enhanced Deep Neural Network (DNN) based learning framework in this paper for Internet-of-Things (IoT), edge, and cloud convergence…

cs.CR202373 cited

Trustworthy Privacy-preserving Hierarchical Ensemble and Federated Learning in Healthcare 4.0 with Blockchain

Veronika Stephanie, Ibrahim Khalil, Mohammed Atiquzzaman +1

The advancement of Internet and Communication Technologies (ICTs) has led to the era of Industry 4.0. This shift is followed by healthcare industries creating the term Healthcare 4…

cs.CR202360 cited

SMPC-based Federated Learning for 6G enabled Internet of Medical Things

Aditya Pribadi Kalapaaking, Veronika Stephanie, Ibrahim Khalil +3

Rapidly developing intelligent healthcare systems are underpinned by Sixth Generation (6G) connectivity, ubiquitous Internet of Things (IoT), and Deep Learning (DL) techniques. Thi…

cs.CR2023160 cited

Blockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammad Saidur Rahman +3

This paper proposes a blockchain-based Federated Learning (FL) framework with Intel Software Guard Extension (SGX)-based Trusted Execution Environment (TEE) to securely aggregate l…