7 citations · 21 across the 9 of their papers we have counts for
9 papers
FedGraph-VASP: Privacy-Preserving Federated Graph Learning with Post-Quantum Security for Cross-Institutional Anti-Money Laundering
Daniel Commey, Matilda Nkoom, Yousef Alsenani +2
Virtual Asset Service Providers (VASPs) face a fundamental tension between regulatory compliance and user privacy when detecting cross-institutional money laundering. Current appro…
FedSkipTwin: Digital-Twin-Guided Client Skipping for Communication-Efficient Federated Learning
Daniel Commey, Kamel Abbad, Garth V. Crosby +1
Communication overhead remains a primary bottleneck in federated learning (FL), particularly for applications involving mobile and IoT devices with constrained bandwidth. This work…
ZKP-FedEval: Verifiable and Privacy-Preserving Federated Evaluation using Zero-Knowledge Proofs
Daniel Commey, Benjamin Appiah, Griffith S. Klogo +1
Federated Learning (FL) enables collaborative model training on decentralized data without exposing raw data. However, the evaluation phase in FL may leak sensitive information thr…
A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning
Daniel Commey, Rebecca A. Sarpong, Griffith S. Klogo +2
Federated learning (FL) enables collaborative model training across decentralized clients while preserving data privacy. However, its open-participation nature exposes it to data-p…
PQS-BFL: A Post-Quantum Secure Blockchain-based Federated Learning Framework
Daniel Commey, Garth V. Crosby
Federated Learning (FL) enables collaborative model training while preserving data privacy, but its classical cryptographic underpinnings are vulnerable to quantum attacks. This vu…
Strategic Deployment of Honeypots in Blockchain-based IoT Systems
Daniel Commey, Sena Hounsinou, Garth V. Crosby
This paper addresses the challenge of enhancing cybersecurity in Blockchain-based Internet of Things (BIoTs) systems, which are increasingly vulnerable to sophisticated cyberattack…
Securing Blockchain-based IoT Systems with Physical Unclonable Functions and Zero-Knowledge Proofs
Daniel Commey, Sena Hounsinou, Garth V. Crosby
This paper presents a framework for securing blockchain-based IoT systems by integrating Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs (ZKPs) within a Hyperledger…
EGAN: Evolutional GAN for Ransomware Evasion
Daniel Commey, Benjamin Appiah, Bill K. Frimpong +3
Adversarial Training is a proven defense strategy against adversarial malware. However, generating adversarial malware samples for this type of training presents a challenge becaus…
Securing Health Data on the Blockchain: A Differential Privacy and Federated Learning Framework
Daniel Commey, Sena Hounsinou, Garth V. Crosby
This study proposes a framework to enhance privacy in Blockchain-based Internet of Things (BIoT) systems used in the healthcare sector. The framework addresses the challenge of lev…