most citedPrivacy-Preserving and Outsourced Multi-User k-Means Clustering

4 citations · 5 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CR2023

A Multi-Client Searchable Encryption Scheme for IoT Environment

Nazatul H. Sultan, Shabnam Kasra-Kermanshahi, Yen Tran +4

The proliferation of connected devices through Internet connectivity presents both opportunities for smart applications and risks to security and privacy. It is vital to proactivel…

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.CR2023113 cited

Blockchain-based Federated Learning with SMPC Model Verification Against Poisoning Attack for Healthcare Systems

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Xun Yi

Due to the rising awareness of privacy and security in machine learning applications, federated learning (FL) has received widespread attention and applied to several areas, e.g.,…

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…

cs.CR20144 cited

Privacy-Preserving and Outsourced Multi-User k-Means Clustering

Bharath K. Samanthula, Fang-Yu Rao, Elisa Bertino +2

Many techniques for privacy-preserving data mining (PPDM) have been investigated over the past decade. Often, the entities involved in the data mining process are end-users or orga…