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Outputs (43)

Reliability Analysis of Fault Tolerant Memory Systems (2023)
Conference Proceeding
Yigit, Y., Maglaras, L., Amine Ferrag, M., Moradpoor, N., & Lambropoulos, G. (2023). Reliability Analysis of Fault Tolerant Memory Systems. In 2023 8th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM). https://doi.org/10.1109/SEEDA-CECNSM61561.2023.10470763

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.

Machine Learning for Smart Healthcare Management Using IoT (2023)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (in press). Machine Learning for Smart Healthcare Management Using IoT. In IoT and ML for Information Management: A Smart Healthcare Perspective. Springer

The convergence of Machine Learning (ML) and the Internet of Things (IoT) has brought about a paradigm shift in healthcare, ushering in a new era of intelligent healthcare management. This powerful amalgamation is driving transformative changes acros... Read More about Machine Learning for Smart Healthcare Management Using IoT.

Enhancing Mac OS Malware Detection through Machine Learning and Mach-O File Analysis (2023)
Conference Proceeding
Thaeler, A., Yigit, Y., Maglaras, L. A., Buchanan, B., Moradpoor, N., & Russell, G. (in press). Enhancing Mac OS Malware Detection through Machine Learning and Mach-O File Analysis. In 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

The Threat of Adversarial Attacks Against Machine Learning-based Anomaly Detection Approach in a Clean Water Treatment System (2023)
Conference Proceeding
Moradpoor, N., Maglaras, L., Abah, E., & Robles-Durazno, A. (2023). The Threat of Adversarial Attacks Against Machine Learning-based Anomaly Detection Approach in a Clean Water Treatment System. In 2023 19th IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (453-460). https://doi.org/10.1109/DCOSS-IoT58021.2023.00077

The protection of Critical National Infrastructure is extremely important due to nations being dependent on their operation and steadiness. Any disturbance to this infrastructure could have a devastating consequence on physical security, economic wel... Read More about The Threat of Adversarial Attacks Against Machine Learning-based Anomaly Detection Approach in a Clean Water Treatment System.

A Blockchain-based two Factor Honeytoken Authentication System (2023)
Presentation / Conference
Papaspirou, V., Maglaras, L., Kantzavelou, I., Moradpoor, N., & Katsikas, S. (2023, September). A Blockchain-based two Factor Honeytoken Authentication System. Poster presented at 28th European Symposium on Research in Computer Security (ESORICS), The Hague

This paper extends and advances our recently introduced two-factor Honeytoken authentication method by incorporating blockchain technology. This novel approach strengthens the authentication method, preventing various attacks, including tampering att... Read More about A Blockchain-based two Factor Honeytoken Authentication System.

A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks (2023)
Journal Article
Khan, N. W., Alshehri, M. S., Khan, M. A., Almakdi, S., Moradpoor, N., Alazeb, A., …Ahmad, J. (2023). A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks. Mathematical Biosciences and Engineering, 20(8), 13491-13520. https://doi.org/10.3934/mbe.2023602

The Internet of Things (IoT) is a rapidly evolving technology with a wide range of potential applications, but the security of IoT networks remains a major concern. The existing system needs improvement in detecting intrusions in IoT networks. Severa... Read More about A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks.

Fake PLC in the cloud, we thought the attackers believed that: How ICS honeypot deception gets impacted by cloud deployments? (2023)
Conference Proceeding
Ivanova, S., & Moradpoor, N. (2023). Fake PLC in the cloud, we thought the attackers believed that: How ICS honeypot deception gets impacted by cloud deployments?. In 2023 IEEE 19th International Conference on Factory Communication Systems (WFCS) (217-220). https://doi.org/10.1109/WFCS57264.2023.10144119

The Industrial Control System (ICS) industry faces an ever-growing number of cyber threats - defence against which can be strengthened using honeypots. As the systems they mimic, ICS honeypots shall be deployed in a similar context to field ICS syste... Read More about Fake PLC in the cloud, we thought the attackers believed that: How ICS honeypot deception gets impacted by cloud deployments?.

Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain (2023)
Conference Proceeding
Moradpoor, N., Barati, M., Robles-Durazno, A., Abah, E., & McWhinnie, J. (2023). Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain. In Proceedings of the International Conference on Cybersecurity, Situational Awareness and Social Media (437-451). https://doi.org/10.1007/978-981-19-6414-5_24

The protection of critical national infrastructures such as drinking water, gas, and electricity is extremely important as nations are dependent on their operation and steadiness. However, despite the value of such utilities their security issues hav... Read More about Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain.