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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?.

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. (in press). 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)

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.

Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets (2022)
Conference Proceeding
Alharigy, L. M., Al-Nuaim, H. A., & Moradpoor, N. (2022). Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets. In 2022 14th International Conference on Computational Intelligence and Communication Networks (CICN). https://doi.org/10.1109/CICN56167.2022.10008274

Cyberbullying is a widespread problem that has only increased in recent years due to the massive dependence on social media. Although, there are many approaches for detecting cyberbullying they still need to be improved upon for more accurate detecti... Read More about Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets.

Building Towards Automated Cyberbullying Detection: A Comparative Analysis (2022)
Journal Article
Al Harigy, L. M., Al Nuaim, H. A., Moradpoor, N., & Tan, Z. (2022). Building Towards Automated Cyberbullying Detection: A Comparative Analysis. Computational Intelligence and Neuroscience, 2022, Article 4794227. https://doi.org/10.1155/2022/4794227

The increased use of social media between digitally anonymous users, sharing their thoughts and opinions, can facilitate participation and collaboration. However, it’s this anonymity feature which gives users freedom of speech and allows them to cond... Read More about Building Towards Automated Cyberbullying Detection: A Comparative Analysis.

Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles (2021)
Conference Proceeding
Cutajar, O., Moradpoor, N., & Jaroucheh, Z. (2021). Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles. In 2021 14th International Conference on Security of Information and Networks (SIN). https://doi.org/10.1109/SIN54109.2021.9699326

In a perfect world, coordination and cooperation across distributed autonomous systems would be a trivial task. However, incomplete information, malicious actors and real-world conditions can provide challenges which bring the trust-worthiness of par... Read More about Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles.

VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems (2021)
Conference Proceeding
Robles Durazno, A., Moradpoor, N., McWhinnie, J., & Porcel-Bustamante, J. (2021). VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems. In 2021 14th International Conference on Security of Information and Networks (SIN). https://doi.org/10.1109/SIN54109.2021.9699375

The rapid development of technology during the last decades has led to the integration of the network capabilities in the devices that are essential in the operation of Industrial Control Systems (ICS). Consequently, the attack surface of these asset... Read More about VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems.

Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System   (2021)
Journal Article
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Tan, Z. (2021). Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System  . Ad hoc networks, 120, Article 102590. https://doi.org/10.1016/j.adhoc.2021.102590

Industrial Control Systems (ICS) are hardware, network, and software, upon which a facility depends to allow daily operations to function. In most cases society takes the operation of such systems, for example public transport, tap water or electrici... Read More about Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System  .

Implementation and Evaluation of Physical, Hybrid, and Virtual Testbeds for Cybersecurity Analysis of Industrial Control Systems (2021)
Journal Article
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Porcel-Bustamante, J. (2021). Implementation and Evaluation of Physical, Hybrid, and Virtual Testbeds for Cybersecurity Analysis of Industrial Control Systems. Symmetry, 13(3), Article 519. https://doi.org/10.3390/sym13030519

Industrial Control Systems are an essential part of our daily lives and can be found in industries such as oil, utilities, and manufacturing. Rapid growth in technology has introduced industrial components with network capabilities that allow them to... Read More about Implementation and Evaluation of Physical, Hybrid, and Virtual Testbeds for Cybersecurity Analysis of Industrial Control Systems.

Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features (2020)
Conference Proceeding
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2020). Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.9207462

Industrial Control Systems have become a priority domain for cybersecurity practitioners due to the number of cyber-attacks against those systems has increased over the past few years. This paper proposes a real-time anomaly intrusion detector for a... Read More about Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features.

Insider Threat Detection Using Supervised Machine Learning Algorithms on an Extremely Imbalanced Dataset (2020)
Journal Article
Moradpoor, N., & Hall, A. (2020). Insider Threat Detection Using Supervised Machine Learning Algorithms on an Extremely Imbalanced Dataset. International Journal of Cyber Warfare and Terrorism, 10(2), https://doi.org/10.4018/IJCWT.2020040101

An insider threat can take on many forms and fall under different categories. This includes: malicious insider, careless/unaware/uneducated/naïve employee, and third-party contractor. A malicious insider, which can be a criminal agent recruited as a... Read More about Insider Threat Detection Using Supervised Machine Learning Algorithms on an Extremely Imbalanced Dataset.

Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset (2020)
Journal Article
Foley, J., Moradpoor, N., & Ochen, H. (2020). Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset. Security and Communication Networks, 2020, Article 2804291. https://doi.org/10.1155/2020/2804291

One of the important features of Routing Protocol for Low-Power and Lossy Networks (RPL) is Objective Function (OF). OF influences an IoT network in terms of routing strategies and network topology. On the other hand, detecting a combination of attac... Read More about Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks Against Two Objective Functions Using a Novel Dataset.

WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels (2019)
Conference Proceeding
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2019). WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels. In Proceedings of 15th IEEE International Conference on Control & Automation (ICCA). https://doi.org/10.1109/ICCA.2019.8899564

Industrial Control Systems (ICS) have faced a growing number of threats over the past few years. Reliance on isolated controls networks or air-gapped computers is no longer a feasible solution when it comes to protecting ICS. It is because the new ar... Read More about WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels.

PLC Memory Attack Detection and Response in a Clean Water Supply System (2019)
Journal Article
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Maneru-Marin, I. (2019). PLC Memory Attack Detection and Response in a Clean Water Supply System. International Journal of Critical Infrastructure Protection, 26, https://doi.org/10.1016/j.ijcip.2019.05.003

Industrial Control Systems (ICS) are frequently used in manufacturing and critical infrastructures like water treatment, chemical plants, and transportation schemes. Citizens tend to take modern-day conveniences such as trains, planes or tap water fo... Read More about PLC Memory Attack Detection and Response in a Clean Water Supply System.

Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier (2019)
Conference Proceeding
Hall, A. J., Pitropakis, N., Buchanan, W. J., & Moradpoor, N. (2019). Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier. In 2018 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData.2018.8621922

Insider threats continue to present a major challenge for the information security community. Despite constant research taking place in this area; a substantial gap still exists between the requirements of this community and the solutions that are cu... Read More about Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier.

Implementation and Detection of Novel Attacks to the PLC Memory on a Clean Water Supply System (2018)
Conference Proceeding
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Maneru-Marin, I. (2019). Implementation and Detection of Novel Attacks to the PLC Memory on a Clean Water Supply System. In CITT 2018 (91-103). https://doi.org/10.1007/978-3-030-05532-5_7

Critical infrastructures such as nuclear plants or water supply systems are mainly managed through electronic control systems. Such systems comprise of a number of elements, such as programmable logic controllers (PLC), networking devices, and actua... Read More about Implementation and Detection of Novel Attacks to the PLC Memory on a Clean Water Supply System.

A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system (2018)
Conference Proceeding
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2018). A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. In Proceedings of the IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2018). https://doi.org/10.1109/CyberSecPODS.2018.8560683

Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development over time have improved their components including operating system platforms... Read More about A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system.

Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things (2018)
Conference Proceeding
Semedo, F., Moradpoor, N., & Rafiq, M. (2018). Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things. In SIN '18 Proceedings of the 11th International Conference on Security of Information and Networks. https://doi.org/10.1145/3264437.3264438

The Internet of Things (IoT) can be described as the ever-growing global network of objects with built-in sensing and communication interfaces such as sensors, Global Positioning devices (GPS) and Local Area Network (LAN) interfaces. Security is by f... Read More about Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things.