Outputs (60)

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, May). Post-Quantum ZKP for Privacy-Preserving Authentication and Model Verification in Decentralized CAV. Presented at CCNI 2025: 3rd International Workshop on Cybersecurity of Critical National Infrastructures (co-organized with IEEE WOWMOM 2025), Fort Worth, Texas

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.

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, August). Privacy-Preserving Knowledge Graph Sharing in Peer-to-Peer Decentralized Federated Learning for Connected Autonomous Vehicles. Presented at ARES '25: 20th International Conference on Availability, Reliability and Security, Ghent, Belgium

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.

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, June). Binius Zero-Knowledge Proofs Meet Multi-Layer Bloom Filters: A Secure and Efficient Protocol for Federated Learning in Autonomous Vehicle Networks. Presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

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, June). A Blockchain-Powered Defence System Against DDoS Attacks with Incentivised Collaboration. Presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

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.

A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection (2025)
Presentation / Conference Contribution
Zeeshan, N., Spada, L. L., & Moradpoor, N. (2025, June). A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection. Presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

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., Maglaras, L., Moradpoor, N., Kioskli, K., Buchanan, W., & Canberk, B. (2025, June). Ransomware: Analysis and Evaluation of Live Forensic Techniques and the Impact on Linux Based IoT Systems. Presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

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., Moradpoor, N., & Canberk, B. (2025, June). ARSecure: A Novel End-to-End Encryption Messaging System Using Augmented Reality. Poster presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

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.

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), Article 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), Article 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 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. (2024, December). Enhancing Security and Privacy in Federated Learning for Connected Autonomous Vehicles with Lightweight Blockchain and Binius Zero- Knowledge Proofs. Presented at 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia

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.