Daniel Commey

Ph.D. Candidate (Dissertation Defended)

dcommey [AT] tamu.edu

CV

Bio

I am a Ph.D. Candidate (Dissertation Defended) in Interdisciplinary Engineering at Texas A&M University, USA, advised by Dr. Garth V. Crosby. My research focuses on networking and cybersecurity for blockchain, IoT, and cloud/edge systems, with applications in FinTech and healthcare.

Prior to my Ph.D., I was an Assistant Lecturer at Ho Technical University, Ghana. I hold an M.Phil. and a B.Sc. in Computer Engineering from KNUST, Ghana, and a B.Tech. in Accounting with Computing from Kumasi Technical University.

My dissertation, "A Layered Security Framework for Blockchain-Based IoT Systems," introduces a defense-in-depth strategy addressing security gaps across device, network, and data layers. My contributions include PUFZIN, a device authentication protocol utilizing Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs; BHICS, an adaptive intrusion detection system using dynamic honeypots and machine learning; and PQS-BFL, a post-quantum secure federated learning framework designed to protect long-term data integrity against future quantum threats.

Research Interests

  • Areas: Networking and cybersecurity for blockchain, IoT, and cloud/edge systems.
  • Methods: Applied cryptography (ZKPs), federated/decentralized learning, ML for network security, game-theoretic models.

Teaching Interests

  • Computer Networks, Network Security, Cybersecurity
  • Digital Systems, Embedded Systems
  • Programming (C/C++, Python), Intro to Computer Engineering

Research Projects

Key contributions from my dissertation on layered security for blockchain-based IoT systems:

PUFZIN

A device authentication protocol utilizing Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs for secure blockchain-IoT integration.

PUF Zero-Knowledge Proofs IoT Security Blockchain
View Paper Code

BHICS

An adaptive Blockchain-based Honeypot Intrusion Detection System using dynamic honeypot conversion and machine learning for resource-efficient IoT security.

Honeypots Intrusion Detection Machine Learning Game Theory
View Paper Code

PQS-BFL

A post-quantum secure federated learning framework for blockchain-based healthcare systems, designed to protect long-term data integrity against quantum threats.

Post-Quantum Cryptography Federated Learning Healthcare Blockchain
View Paper Code

News

Publications

Game-Theoretic Analysis of MEV Attacks and Mitigation Strategies in Decentralized Finance

B. Appiah, Daniel Commey, W. Bagyl-Bac, L. Adjei, E. Owusu

Analytics, 2025

Paper

Blockchain-enabled dynamic honeypot conversion for resource-efficient IoT security

Daniel Commey, M. Nkoom, S. G. Hounsinou, G. V. Crosby

Journal of Information Security and Applications, 2025

Paper

Post-Quantum Secure Blockchain-Based Federated Learning Framework for Healthcare Analytics

Daniel Commey, S. G. Hounsinou, G. V. Crosby

IEEE Networking Letters, 2025

Paper

Secure IoT firmware updates against supply chain attacks

B. Appiah, Daniel Commey, I. Osei, B. K. Frimpong, G. Assamah, E. N. A. Hammond

The Journal of Supercomputing, 2025

Paper

Enhanced federated learning for secure medical data collaboration

B. Appiah, I. Osei, B. K. Frimpong, Daniel Commey, K. Owusu-Agymang, G. Assamah

Journal of Analytical Science and Technology, 2025

Paper

Securing Blockchain-Based IoT Systems: A Review

Daniel Commey, B. Mai, S. G. Hounsinou, G. V. Crosby

IEEE Access, vol. 12, pp. 98856--98881, 2024

Paper

Performance Comparison of 3DES, AES, Blowfish and RSA for Dataset Classification and Encryption in Cloud Data Storage

Daniel Commey, Selorm Griffith, James Dzisi

International Journal of Computer Applications, 177(40), 17--22, 2020

Paper

Federated DDoS Detection with Clustered Quantization-Aware Training Models for IoRT

Daniel Commey, B. Appiah, B. K. Frimpong, I. Osei, E. N. A. Hammond, G. V. Crosby

2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA (to appear)

FedSkipTwin: Digital-Twin-Guided Client Skipping for Communication-Efficient Federated Learning

Daniel Commey, K. Abbad, G. V. Crosby, L. Khoukhi

2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA (to appear)

A Unified Lightweight Benchmark for Privacy-Preserving Federated Learning in Cyber-Physical Systems (Fashion-MNIST Case Study)

Daniel Commey, B. Ockman, G. V. Crosby

IEEE Workshop on 7th Security Trust Privacy for Cyber-Physical Systems (STP-CPS), co-located with 2026 IEEE CCNC (to appear)

Resource-Aware Clustered Federated Learning for Industrial Digital Twins: A Reproducible Benchmark on Fashion-MNIST

Daniel Commey, U. Hamid, D. Sung, G. V. Crosby

Workshop on Industrial Digital Twins and Emerging Technologies, co-located with 2026 IEEE CCNC (to appear)

Robotic Algorithm Service Contracts to Manage and Incentivize Adaptive Behavior

S. Mallikarachchi, P. Thammi, Daniel Commey, S. S. Vitharana, M. Chintalapati, I. S. Godage

2025 7th International Conference on Blockchain Computing and Applications (BCCA), Dubrovnik, Croatia

Paper

Securing Blockchain-based IoT Systems with Physical Unclonable Functions and Zero-Knowledge Proofs

Daniel Commey, S. G. Hounsinou, G. V. Crosby

2024 IEEE 49th Conference on Local Computer Networks (LCN), Normandy, France

Paper

Securing the Internet of Robotic Things: A Federated Learning Approach

M. Nkoom, Daniel Commey, S. G. Hounsinou, G. V. Crosby

2024 IEEE 49th Conference on Local Computer Networks (LCN), Normandy, France

Paper

Strategic Deployment of Honeypots in Blockchain-based IoT Systems

Daniel Commey, S. G. Hounsinou, G. V. Crosby

2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS), Abu Dhabi, UAE

Paper

EGAN: Evolutional GAN for Ransomware Evasion

Daniel Commey, B. Appiah, B. K. Frimpong, I. Osei, E. N. A. Hammond, G. V. Crosby

2023 IEEE 48th Conference on Local Computer Networks (LCN), Daytona Beach, FL, USA

Paper

FedSkipTwin: Digital-Twin-Guided Client Skipping for Communication-Efficient Federated Learning

Daniel Commey, K. Abbad, G. V. Crosby, L. Khoukhi

arXiv:2507.13624 [cs.LG], 2025; also accepted at 2026 IEEE CCNC

Preprint

ZKP-FedEval: Verifiable and Privacy-Preserving Federated Evaluation using Zero-Knowledge Proofs

Daniel Commey, B. Appiah, G. S. Klogo, G. V. Crosby

arXiv:2507.11649 [cs.LG], 2025

Preprint

A Bayesian Incentive Mechanism for Poison-Resilient Federated Learning

Daniel Commey, R. A. Sarpong, G. S. Klogo, W. Bagyl-Bac, G. V. Crosby

arXiv:2507.12439 [cs.LG], 2025

Preprint

Performance Analysis and Deployment Considerations of Post-Quantum Cryptography for Consumer Electronics

Daniel Commey, B. Appiah, G. S. Klogo, W. Bagyl-Bac, J. D. Gadze

arXiv:2505.02239 [cs.CR], 2025

Preprint

Pufzin: Secure and Scalable Blockchain-IoT with PUFs and Zero-Knowledge Proofs

Daniel Commey, S. G. Hounsinou, G. V. Crosby

SSRN Preprint

Preprint

Securing Health Data on the Blockchain: A Differential Privacy and Federated Learning Framework

Daniel Commey, S. G. Hounsinou, G. V. Crosby

arXiv:2405.11580 [cs.CR], 2024

Preprint

Résumé

My full CV is available here.

Daniel Commey, Ph.D.
Based on the template by Martin Saveski and Paul J. Wright.