All Outputs (32)

Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain (2023)
Presentation / Conference Contribution
Moradpoor, N., Barati, M., Robles-Durazno, A., Abah, E., & McWhinnie, J. (2022, June). Neutralising Adversarial Machine Learning in Industrial Control Systems Using Blockchain. Presented at Cyber Science 2022: International Conference on Cybersecurity, Situational Awareness and Social Media, Cardiff Metropolitan University, Wales

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)
Presentation / Conference Contribution
Alharigy, L. M., Al-Nuaim, H. A., & Moradpoor, N. (2022, December). Deep Pre-trained Contrastive Self-Supervised Learning: A Cyberbullying Detection Approach with Augmented Datasets. Presented at 2022 14th International Conference on Computational Intelligence and Communication Networks (CICN), Al Khobar, Saudi Arabia

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.

VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems (2021)
Presentation / Conference Contribution
Robles Durazno, A., Moradpoor, N., McWhinnie, J., & Porcel-Bustamante, J. (2021, December). VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems. Presented at SINCONF 2021: 14th International Conference on Security of Information and Networks, Edinburgh (Online)

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.

Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles (2021)
Presentation / Conference Contribution
Cutajar, O., Moradpoor, N., & Jaroucheh, Z. (2021, December). Using IOTA as an Inter-Vehicular Trust Mechanism in Autonomous Vehicles. Presented at SINCONF 2021: 14th International Conference on Security of Information and Networks, Edinburgh (Online)

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.

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)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2020, July). Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features. Presented at International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK

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)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2019, July). WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels. Presented at 15th IEEE International Conference on Control & Automation (ICCA), Edinburgh, Scotland

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.

Implementation and Detection of Novel Attacks to the PLC Memory on a Clean Water Supply System (2018)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Maneru-Marin, I. (2018, August). Implementation and Detection of Novel Attacks to the PLC Memory on a Clean Water Supply System. Presented at The 4th International Conference on Technology Trends, Babahoyo, Ecuador

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)
Presentation / Conference Contribution
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2018, June). A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. Presented at Cyber Security 2018: 2018 International Conference on Cyber Security and Protection of Digital Services, Glasgow, United Kingdom

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)
Presentation / Conference Contribution
Semedo, F., Moradpoor, N., & Rafiq, M. (2018, September). Vulnerability Assessment of Objective Function of RPL Protocol for Internet of Things. Presented at 11th International Conference On Security Of Information and Networks, Cardiff, United Kingdom

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.

Employing machine learning techniques for detection and classification of phishing emails (2018)
Presentation / Conference Contribution
Moradpoor, N., Clavie, B., & Buchanan, B. (2017, July). Employing machine learning techniques for detection and classification of phishing emails. Presented at 2017 Computing Conference, London, UK

A phishing email is a legitimate-looking email which is designed to fool the recipient into believing that it is a genuine email, and either reveals sensitive information or downloads malicious software through clicking on malicious links contained i... Read More about Employing machine learning techniques for detection and classification of phishing emails.

Insider threat detection using principal component analysis and self-organising map (2017)
Presentation / Conference Contribution
Moradpoor, N., Brown, M., & Russell, G. (2017, October). Insider threat detection using principal component analysis and self-organising map. Presented at Proceedings of the 10th International Conference on Security of Information and Networks - SIN '17, India

An insider threat can take on many aspects. Some employees abuse their positions of trust by disrupting normal operations, while others export valuable or confidential data which can damage the employer's marketing position and reputation. In additio... Read More about Insider threat detection using principal component analysis and self-organising map.

A Learning-based Neural Network Model for the Detection and Classification of SQL Injection Attacks (2017)
Journal Article
Sheykhkanloo, N. M. (2017). A Learning-based Neural Network Model for the Detection and Classification of SQL Injection Attacks. International Journal of Cyber Warfare and Terrorism, 7(2), 16-41. https://doi.org/10.4018/ijcwt.2017040102

Structured Query Language injection (SQLi) attack is a code injection technique where hackers inject SQL commands into a database via a vulnerable web application. Injected SQL commands can modify the back-end SQL database and thus compromise the sec... Read More about A Learning-based Neural Network Model for the Detection and Classification of SQL Injection Attacks.

A survey of Intrusion Detection System technologies (2016)
Presentation / Conference Contribution
Heenan, R., & Moradpoor, N. (2016). A survey of Intrusion Detection System technologies. In PGCS 2016: The First Post Graduate Cyber Security Symposium – The Cyber Academy

This paper provides an overview of IDS types and how they work as well as configuration considerations and issues that affect them. Advanced methods of increasing the performance of an IDS are explored such as specification based IDS for protecting S... Read More about A survey of Intrusion Detection System technologies.

Introduction to Security Onion (2016)
Presentation / Conference Contribution
Heenan, R., & Moradpoor, N. (2016, May). Introduction to Security Onion. Paper presented at Post Graduate Cyber Security (PGCS) symposium

Security Onion is a Network Security Manager (NSM) platform that provides multiple Intrusion Detection Systems (IDS) including Host IDS (HIDS) and Network IDS (NIDS). Many types of data can be acquired using Security Onion for analysis. This includes... Read More about Introduction to Security Onion.