All Outputs (14)

AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks (2024)
Journal Article
Yigit, Y., Maglaras, L., Buchanan, W. J., Canberk, B., Shin, H., & Duong, T. Q. (2024). AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks. IEEE Internet of Things, 11(22), 36168-36181. https://doi.org/10.1109/jiot.2024.3455089

Digital twin technology is crucial to the development of the sixth-generation (6G) Internet of Vehicles (IoV) as it allows the monitoring and assessment of the dynamic and complicated vehicular environment. However, 6G IoV networks have critical chal... Read More about AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks.

Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities (2024)
Journal Article
Yigit, Y., Ahmadi, H., Yurdakul, G., Canberk, B., Hoang, T., & Duong, T. Q. (2024). Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities. IEEE Communications Standards Magazine, 8(3), 28-34. https://doi.org/10.1109/mcomstd.0002.2300027

Digital twin (DT)-based smart cities are anticipated to achieve seamless integration between physical and digital objects to satisfy an enormous number of users across all domains. Therefore, the infrastructure of 6G smart cities has become an import... Read More about Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities.

Autonomous Queue Management System in Software-defined Routers for Sensor Networks (2024)
Presentation / Conference Contribution
Yigit, Y., Maglaras, L., Karantzalos, K., Gursu, K., Ozdem, M., Buchanan, W. J., & Canberk, B. (2024, November). Autonomous Queue Management System in Software-defined Routers for Sensor Networks. Paper presented at 2024 IEEE 10th World Forum on Internet of Things (WF-IoT), Ottawa, Canada

Recent advancements in sensor networks, the In-ternet of Things (IoT), and machine communication technologies have led to a significant increase in network traffic across various domains. However, this growth has brought forth the critical challenge... Read More about Autonomous Queue Management System in Software-defined Routers for Sensor Networks.

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. In IoT and ML for Information Management: A Smart Healthcare Perspective (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.

PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme (2024)
Presentation / Conference Contribution
Yaqub, Z., Yigit, Y., Maglaras, L., Tan, Z., & Wooderson, P. (2024, April). PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme. Presented at The 20th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2024), Abu Dhabi, UAE

In the rapidly evolving landscape of Intelligent Transportation Systems (ITS), Vehicular Ad-hoc Networks (VANETs) play a critical role in enhancing road safety and traffic flow. However, VANETs face significant security and privacy challenges due to... Read More about PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme.

A Blockchain-based Multi-Factor Honeytoken Dynamic Authentication Mechanism (2024)
Presentation / Conference Contribution
Papaspirou, V., Kantzavelou, I., Yigit, Y., Maglaras, L., & Katsikas, S. (2024, July). A Blockchain-based Multi-Factor Honeytoken Dynamic Authentication Mechanism. Presented at ARES 2024: The 19th International Conference on Availability, Reliability and Security, Vienna, Austria

The evolution of authentication mechanisms in ensuring secure access to systems has been crucial for mitigating vulnerabilities and enhancing system security. However, despite advancements in two-factor authentication (2FA) and multi-factor authentic... Read More about A Blockchain-based Multi-Factor Honeytoken Dynamic Authentication Mechanism.

Enhancing Cybersecurity Training Efficacy: A Comprehensive Analysis of Gamified Learning, Behavioral Strategies and Digital Twins (2024)
Presentation / Conference Contribution
Yigit, Y., Kioskli, K., Bishop, L., Chouliaras, N., Maglaras, L., & Janicke, H. (2024, June). Enhancing Cybersecurity Training Efficacy: A Comprehensive Analysis of Gamified Learning, Behavioral Strategies and Digital Twins. Presented at 2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Perth, Australia

This paper delves into enhancing cybersecurity training efficacy through an in-depth examination of gamified learning, behavioural strategies, and the deployment of digital twins. It identifies the critical role of behavioural strategies in bolsterin... Read More about Enhancing Cybersecurity Training Efficacy: A Comprehensive Analysis of Gamified Learning, Behavioral Strategies and Digital Twins.

Cyber-Twin: Digital Twin-Boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks (2024)
Presentation / Conference Contribution
Yigit, Y., Panitsas, I., Maglaras, L., Tassiulas, L., & Canberk, B. (2024, June). Cyber-Twin: Digital Twin-Boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks. Presented at ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA

The rapid evolution of Vehicular Ad-hoc NETworks (VANETs) has ushered in a transformative era for intelligent transportation systems (ITS), significantly enhancing road safety and vehicular communication. However, the intricate and dynamic nature of... Read More about Cyber-Twin: Digital Twin-Boosted Autonomous Attack Detection for Vehicular Ad-Hoc Networks.

Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing (2024)
Presentation / Conference Contribution
Babaghayou, M., Chaib, N., Maglaras, L., Yigit, Y., Ferrag, M. A., & Marsh, C. (2023, December). Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing. Presented at 16th EAI International Conference, WiCON 2023, Athens, Greece

In an era of rapidly evolving mobile computing, integrating satellite technologies with the Internet of Things (IoT) creates new communication and data management horizons. Our research focuses on the emerging challenge of efficiently managing heavy... Read More about Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing.

Reliability Analysis of Fault Tolerant Memory Systems (2023)
Presentation / Conference Contribution
Yigit, Y., Maglaras, L., Amine Ferrag, M., Moradpoor, N., & Lambropoulos, G. (2023, November). Reliability Analysis of Fault Tolerant Memory Systems. Presented at The 8th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2023), Piraeus, Greece

This paper delves into a comprehensive analysis of fault-tolerant memory systems, focusing on recovery techniques modelled using Markov chains to address transient errors. The study revolves around the application of scrubbing methods in conjunction... Read More about Reliability Analysis of Fault Tolerant Memory Systems.

Enhancing Mac OS Malware Detection through Machine Learning and Mach-O File Analysis (2023)
Presentation / Conference Contribution
Thaeler, A., Yigit, Y., Maglaras, L. A., Buchanan, B., Moradpoor, N., & Russell, G. (2023, November). Enhancing Mac OS Malware Detection through Machine Learning and Mach-O File Analysis. Presented at IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMDAD) 2023, Edinburgh, UK

Malware research has predominantly focused on Windows and Android Operating Systems (OS), leaving Mac OS malware relatively unexplored. This paper addresses the growing threat of Mac OS malware by leveraging Machine Learning (ML) techniques. We propo... Read More about Enhancing Mac OS Malware Detection through Machine Learning and Mach-O File Analysis.

Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks (2023)
Presentation / Conference Contribution
Yigit, Y., Chrysoulas, C., Yurdakul, G., Maglaras, L., & Canberk, B. (2023, December). Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks. Presented at 2023 IEEE Globecom Workshops (GC Wkshps): Workshop on Enabling Security, Trust, and Privacy in 6G Wireless Systems, Kuala Lumpur, Malaysia

As global Internet of Things (IoT) devices connectivity surges, a significant portion gravitates towards the Edge of Things (EoT) network. This shift prompts businesses to deploy infrastructure closer to end-users, enhancing accessibility. However, t... Read More about Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks.

TwinPot: Digital Twin-assisted Honeypot for Cyber-Secure Smart Seaports (2023)
Presentation / Conference Contribution
Yigit, Y., Kinaci, O. K., Duong, T. Q., & Canberk, B. (2023, May). TwinPot: Digital Twin-assisted Honeypot for Cyber-Secure Smart Seaports. Presented at 2023 IEEE International Conference on Communications Workshops (ICC Workshops), Rome, Italy

The idea of next-generation ports has become more apparent in the last ten years-in response to the challenge posed by the rising demand for efficiency and the ever-increasing volume of goods. In this new era of intelligent infrastructure and facilit... Read More about TwinPot: Digital Twin-assisted Honeypot for Cyber-Secure Smart Seaports.

YA-DA: YAng-Based DAta Model for Fine-Grained IIoT Air Quality Monitoring (2022)
Presentation / Conference Contribution
Yigit, Y., Huseynov, K., Ahmadi, H., & Canberk, B. (2022, December). YA-DA: YAng-Based DAta Model for Fine-Grained IIoT Air Quality Monitoring. Presented at 2022 IEEE Globecom Workshops (GC Wkshps), Rio de Janeiro, Brazil

With the development of industrialization, air pollution is also steadily on the rise since both industrial and daily activities generate a massive amount of air pollution. Since decreasing air pollution is critical for citizens' health and well-bein... Read More about YA-DA: YAng-Based DAta Model for Fine-Grained IIoT Air Quality Monitoring.