All Outputs (61)

Continuous Authentication in Resource-Constrained Devices via Biometric and Environmental Fusion (2025)
Journal Article
Zeeshan, N., Bakyt, M., Moradpoor, N., & La Spada, L. (2025). Continuous Authentication in Resource-Constrained Devices via Biometric and Environmental Fusion. Sensors, 25(18), 5711. https://doi.org/10.3390/s25185711

Continuous authentication allows devices to keep checking that the active user is still the rightful owner instead of relying on a single login. However, current methods can be tricked by forging faces, revealing personal data, or draining the batter... Read More about Continuous Authentication in Resource-Constrained Devices via Biometric and Environmental Fusion.

Privacy-Preserving Knowledge Graph Sharing in Peer-to-Peer Decentralized Federated Learning for Connected Autonomous Vehicles (2025)
Presentation / Conference Contribution
Andriambelo, N. H., & Moradpoor, N. (2025). Privacy-Preserving Knowledge Graph Sharing in Peer-to-Peer Decentralized Federated Learning for Connected Autonomous Vehicles. Availability, Reliability and Security (ARES 2025) (pp. 241–258). https://doi.org/10.1007/978-3-032-00639-4_14

We present a decentralized framework that enables privacypreserving knowledge graph sharing and robust federated learning among Connected Autonomous Vehicles (CAVs), without relying on trusted coordinators. Each vehicle constructs a local semantic gr... Read More about Privacy-Preserving Knowledge Graph Sharing in Peer-to-Peer Decentralized Federated Learning for Connected Autonomous Vehicles.

A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection (2025)
Presentation / Conference Contribution
Zeeshan, N., Spada, L. L., & Moradpoor, N. (2025). A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection. 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 737-746). IEEE. https://doi.org/10.1109/DCOSS-IoT65416.2025.00113

With the continuous evolution of the smart environment, the use of Internet services is becoming more common. The increased usage of these services has impacted the traditional network boundaries. This shift has created a need for more flexible, accu... Read More about A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection.

Ransomware: Analysis and Evaluation of Live Forensic Techniques and the Impact on Linux Based IoT Systems (2025)
Presentation / Conference Contribution
Korac, S., Moradpoor, N., Buchanan, W., Canberk, B., Maglaras, L., & Kioskli, K. (2025). Ransomware: Analysis and Evaluation of Live Forensic Techniques and the Impact on Linux Based IoT Systems. 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 507-514). IEEE. https://doi.org/10.1109/DCOSS-IoT65416.2025.00084

Ransomware has been predominantly a threat to Windows systems. But, Linux systems became interesting for cybercriminals and this trend is expected to continue. This endangers IoT ecosystems, whereas many IoT systems are based on Linux (e.g. cloud inf... Read More about Ransomware: Analysis and Evaluation of Live Forensic Techniques and the Impact on Linux Based IoT Systems.

ARSecure: A Novel End-to-End Encryption Messaging System Using Augmented Reality (2025)
Presentation / Conference Contribution
Alsop, H., Alsop, D., Solomon, J., Aumento, L., Butters, M., Millar, C., Maglaras, L., Yigit, Y., Canberk, B., & Moradpoor, N. (2025, June 9-11). ARSecure: A Novel End-to-End Encryption Messaging System Using Augmented Reality [Poster]. IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy. https://doi.org/10.1109/DCOSS-IoT65416.2025.00046

End-to-end encryption (E2EE) ensures that only the intended recipient(s) can read messages. Popular instant messaging (IM) applications such as Signal, WhatsApp, Apple's iMessage, and Telegram claim to offer E2EE. However, client-side scanning (CSS)... Read More about ARSecure: A Novel End-to-End Encryption Messaging System Using Augmented Reality.

Binius Zero-Knowledge Proofs Meet Multi-Layer Bloom Filters: A Secure and Efficient Protocol for Federated Learning in Autonomous Vehicle Networks (2025)
Presentation / Conference Contribution
Andriambelo, H., & Moradpoor, N. (2025). Binius Zero-Knowledge Proofs Meet Multi-Layer Bloom Filters: A Secure and Efficient Protocol for Federated Learning in Autonomous Vehicle Networks. 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 777-784). IEEE. https://doi.org/10.1109/DCOSS-IoT65416.2025.00118

We present a secure and efficient federated learning protocol for autonomous vehicles that resists data leaks, redundancy, and adversarial attacks. Our system combines fast zero-knowledge proofs and compressed Bloom filters to verify updates without... Read More about Binius Zero-Knowledge Proofs Meet Multi-Layer Bloom Filters: A Secure and Efficient Protocol for Federated Learning in Autonomous Vehicle Networks.

A Blockchain-Powered Defence System Against DDoS Attacks with Incentivised Collaboration (2025)
Presentation / Conference Contribution
Rajesh, H., Moradpoor, N., Waqas, M., & Maglaras, L. (2025). A Blockchain-Powered Defence System Against DDoS Attacks with Incentivised Collaboration. 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 721-728). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/DCOSS-IoT65416.2025.00111

Distributed Denial of Service (DDoS) attacks continuously pose a significant threat to online services by overwhelming them, rendering them unavailable to legitimate users. This underscores the need for more sophisticated techniques with robust detec... Read More about A Blockchain-Powered Defence System Against DDoS Attacks with Incentivised Collaboration.

Post-Quantum ZKP for Privacy-Preserving Authentication and Model Verification in Decentralized CAV (2025)
Presentation / Conference Contribution
Andriambelo, N. H., Moradpoor, N., & Maglaras, L. (2025). Post-Quantum ZKP for Privacy-Preserving Authentication and Model Verification in Decentralized CAV. 2025 IEEE 26th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) (pp. 275-280). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WoWMoM65615.2025.00054

Decentralized and Connected Autonomous Vehicle (CAV) networks present significant opportunities for improving road safety, efficiency, and traffic management. However, the widespread deployment of these systems is hindered by critical security and pr... Read More about Post-Quantum ZKP for Privacy-Preserving Authentication and Model Verification in Decentralized CAV.

A Novel TLS-Based Fingerprinting Approach That Combines Feature Expansion and Similarity Mapping (2025)
Journal Article
Thomson, A., Maglaras, L., & Moradpoor, N. (2025). A Novel TLS-Based Fingerprinting Approach That Combines Feature Expansion and Similarity Mapping. Future Internet, 17(3), 120. https://doi.org/10.3390/fi17030120

Malicious domains are part of the landscape of the internet but are becoming more prevalent and more dangerous both to companies and to individuals. They can be hosted on various technologies and serve an array of content, including malware, command... Read More about A Novel TLS-Based Fingerprinting Approach That Combines Feature Expansion and Similarity Mapping.

Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities (2025)
Journal Article
Yigit, Y., Ferrag, M. A., Ghanem, M. C., Sarker, I. H., Maglaras, L. A., Chrysoulas, C., Moradpoor, N., Tihanyi, N., & Janicke, H. (2025). Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities. Sensors, 25(6), 1666. https://doi.org/10.3390/s25061666

Critical National Infrastructures (CNIs)—including energy grids, water systems, transportation networks, and communication frameworks—are essential to modern society yet face escalating cybersecurity threats. This review paper comprehensively analyze... Read More about Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities.

Enhancing AI-Generated Image Detection with a Novel Approach and Comparative Analysis (2025)
Presentation / Conference Contribution
Weir, S., Khan, M. S., Moradpoor, N., & Ahmad, J. (2025). Enhancing AI-Generated Image Detection with a Novel Approach and Comparative Analysis. 2024 17th International Conference on Security of Information and Networks (SIN). IEEE. https://doi.org/10.1109/SIN63213.2024.10871900

This study explores advancements in AI-generated image detection, emphasizing the increasing realism of images, including deepfakes, and the need for effective detection methods. Traditional Convolutional Neural Networks (CNNs) have shown success but... Read More about Enhancing AI-Generated Image Detection with a Novel Approach and Comparative Analysis.

Enhancing Security and Privacy in Federated Learning for Connected Autonomous Vehicles with Lightweight Blockchain and Binius Zero- Knowledge Proofs (2025)
Presentation / Conference Contribution
Andriambelo, N. H., & Moradpoor, N. (2025). Enhancing Security and Privacy in Federated Learning for Connected Autonomous Vehicles with Lightweight Blockchain and Binius Zero- Knowledge Proofs. 2024 17th International Conference on Security of Information and Networks (SIN). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SIN63213.2024.10871337

The rise of autonomous vehicles (AVs) brings with it the need for secure and privacy-preserving machine learning models. Federated learning (FL) allows AVs to collaboratively train models while keeping raw data localized. However, traditional FL syst... Read More about Enhancing Security and Privacy in Federated Learning for Connected Autonomous Vehicles with Lightweight Blockchain and Binius Zero- Knowledge Proofs.

EV-IRP Manager: An Electric Vehicle Incident Response Playbook Manager and Visualizer Toolkit (2025)
Presentation / Conference Contribution
Alpdag, K., Moradpoor, N., Hasina Andriambelo, N., Wooderson, P., & Maglaras, L. (2025). EV-IRP Manager: An Electric Vehicle Incident Response Playbook Manager and Visualizer Toolkit. 2024 17th International Conference on Security of Information and Networks (SIN). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SIN63213.2024.10871811

In the rapidly evolving realm of electric vehicle technology, safeguarding the cybersecurity of both electric vehicles and their charging infrastructure has become fundamental. The integration of electric vehicles and their charging stations into the... Read More about EV-IRP Manager: An Electric Vehicle Incident Response Playbook Manager and Visualizer Toolkit.

Lightweight Blockchain Prototype for Food Supply Chain Management (2025)
Presentation / Conference Contribution
Rusakov, A., Moradpoor, N., & Akbarzadeh, A. (2025). Lightweight Blockchain Prototype for Food Supply Chain Management. 2024 17th International Conference on Security of Information and Networks (SIN). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SIN63213.2024.10871597

The modern food supply chain often involves multiple layers of participants spread across different countries and continents. This complex system offers significant benefits to businesses worldwide; however, it also presents several challenges. One m... Read More about Lightweight Blockchain Prototype for Food Supply Chain Management.

Adversarial Attacks on Supervised Energy-Based Anomaly Detection in Clean Water Systems (2025)
Journal Article
Moradpoor, N., Abah, E., Robles-Durazno, A., & Maglaras, L. (2025). Adversarial Attacks on Supervised Energy-Based Anomaly Detection in Clean Water Systems. Electronics, 14(3), 639. https://doi.org/10.3390/electronics14030639

Critical National Infrastructure includes large networks such as telecommunications, transportation, health services, police, nuclear power plants, and utilities like clean water, gas, and electricity. The protection of these infrastructures is cruci... Read More about Adversarial Attacks on Supervised Energy-Based Anomaly Detection in Clean Water Systems.

Machine Learning for Smart Healthcare Management Using IoT (2024)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (2024). Machine Learning for Smart Healthcare Management Using IoT. IoT and ML for Information Management: A Smart Healthcare Perspective (pp. 135-166). Springer. https://doi.org/10.1007/978-981-97-5624-7_4

This chapter explores the significant impact of Machine Learning (ML) and the Internet of Things (IoT) on smart healthcare management, marking a new era of innovation with enhanced patient care and health outcomes. The fusion of IoT devices for real-... Read More about Machine Learning for Smart Healthcare Management Using IoT.

Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records (2024)
Presentation / Conference Contribution
Noyon, M. S. I., Moradpoor, N., Maglaras, L., & Ahmad, J. (2024). Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records. 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 516-523). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/DCOSS-IoT61029.2024.00082

The health sector stands as one of the most crucial and vulnerable domains, harbouring extensive personal data. Particularly, Electronic Health Records store information in electronic media where users lack control over their data. Unauthorized acces... Read More about Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records.

Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario (2024)
Presentation / Conference Contribution
Adesanya, O. M., Moradpoor, N., Maglaras, L., Lim, I. S., & Ferrag, M. A. (2024). Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario. 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/DCOSS-IoT61029.2024.00087

The rapid growth of Internet of Things technology has introduced an era of numerous interconnected devices, transforming the communication with the physical world. However, the security and privacy of the data generated and stored on these devices ha... Read More about Assessment and Analysis of IoT Protocol Effectiveness in Data Exfiltration Scenario.

Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems (2024)
Presentation / Conference Contribution
Jayadev, V., Moradpoor, N., & Petrovski, A. (2024, July 30-August 2). Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems [Paper presentation]. 19th International Conference on Availability, Reliability and Security (ARES 2024), Vienna, Austria. https://doi.org/10.1145/3664476.3670927

Blockchain technology offers a decentralized and secure platform for addressing various challenges in smart cities and cyber-physical systems, including identity management, trust and transparency, and supply chain management. However, blockchains ar... Read More about Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems.

Towards a cyberbullying detection approach: fine-tuned contrastive self-supervised learning for data augmentation (2024)
Journal Article
Al-Harigy, L. M., Al-Nuaim, H. A., Moradpoor, N., & Tan, Z. (2025). Towards a cyberbullying detection approach: fine-tuned contrastive self-supervised learning for data augmentation. International Journal of Data Science and Analytics, 19(3), 469-490. https://doi.org/10.1007/s41060-024-00607-9

Cyberbullying on social media platforms is pervasive and challenging to detect due to linguistic subtleties and the need for extensive data annotation. We introduce a Deep Contrastive Self-Supervised Learning (DCSSL) model that integrates a Natural L... Read More about Towards a cyberbullying detection approach: fine-tuned contrastive self-supervised learning for data augmentation.