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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.

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.

Two Communities, One Topic: Exploring the British Reddit community split based on perceived biases (2018)
Presentation / Conference
Clavie, B., & Moradpoor, N. (2018, May). Two Communities, One Topic: Exploring the British Reddit community split based on perceived biases. Poster presented at 10th ACM Conference on Web Science, Amsterdam

This article explores a perceived bias between two British reddit communities dedicated to discussing British politics.We analyse the popular sources favoured by each community and study semantic indicators that would be indicative of a bias. Althoug... Read More about Two Communities, One Topic: Exploring the British Reddit community split based on perceived biases.

Employing machine learning techniques for detection and classification of phishing emails (2018)
Conference Proceeding
Moradpoor, N., Clavie, B., & Buchanan, B. (2018). Employing machine learning techniques for detection and classification of phishing emails. In Proceedings of the IEEE Technically Sponsored Computing Conference 2017. https://doi.org/10.1109/SAI.2017.8252096

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)
Conference Proceeding
Moradpoor, N., Brown, M., & Russell, G. (2017). Insider threat detection using principal component analysis and self-organising map. In 10th International Conference on Security of Information and Networks (SIN 2017). https://doi.org/10.1145/3136825.3136859

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)
Conference Proceeding
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
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.

A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks (2015)
Journal Article
Moradpoor Sheykhkanloo, N. (2015). A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 9(6), 1443-1453

Thousands of organisations store important and confidential information related to them, their customers, and their business partners in databases all across the world. The stored data ranges from less sensitive (e.g. first name, last name, date of b... Read More about A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks.

SQL-IDS: evaluation of SQLi attack detection and classification based on machine learning techniques (2015)
Conference Proceeding
Sheykhkanloo, N. M. (2015). SQL-IDS: evaluation of SQLi attack detection and classification based on machine learning techniques. In SIN '15 Proceedings of the 8th International Conference on Security of Information and Networks. https://doi.org/10.1145/2799979.2800011

Structured Query Language injection (SQLi) attack is a code injection technique where malicious SQL statements are inserted into a given SQL database by simply using a web browser. Injected SQL commands can alter the database and thus compromise the... Read More about SQL-IDS: evaluation of SQLi attack detection and classification based on machine learning techniques.

Employing Neural Networks for the Detection of SQL Injection Attack (2014)
Conference Proceeding
Sheykhkanloo, N. M. (2014). Employing Neural Networks for the Detection of SQL Injection Attack. In SIN '14 Proceedings of the 7th International Conference on Security of Information and Networks. https://doi.org/10.1145/2659651.2659675

Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into the SQL database by simply using web browsers. SQLI attack can cause severe damages on a given SQL database such as lo... Read More about Employing Neural Networks for the Detection of SQL Injection Attack.

PGCert-2014 Academic Paper and Pedagogy model outline (2014)
Presentation / Conference
Sheykhkanloo, N. M. (2014, October). PGCert-2014 Academic Paper and Pedagogy model outline. Paper presented at Teaching and Learning Enhancement Conference

This paper aims to explore the development of the Abertay Graduate Attributes (AGAs) into one of the computing modules, Issues in Network Security, for third year digital forensic students in school of Science Engineering and Technology (SET) at Univ... Read More about PGCert-2014 Academic Paper and Pedagogy model outline.

A semi-independent structure for the architectural design of the converged scenario for integrated hybrid PON with wireless technologies for next generation broadband access networks (2014)
Conference Proceeding
Moradpoor, N. (2014). A semi-independent structure for the architectural design of the converged scenario for integrated hybrid PON with wireless technologies for next generation broadband access networks. In Proceedings of the 2013 2nd International Workshop on Optical Wireless Communications (IWOW). https://doi.org/10.1109/iwow.2013.6777781

Optical and wireless technology integration schemes merge the high-speed and high-capacity of the optical networks with the low-cost, wide-coverage and mobility features of wireless counterparts for Subscriber Stations (SSs). It is also financially v... Read More about A semi-independent structure for the architectural design of the converged scenario for integrated hybrid PON with wireless technologies for next generation broadband access networks.

A mathematical model for a GA-based dynamic excess bandwidth allocation algorithm for hybrid PON and wireless technology integrations for next generation broadband access networks (2013)
Conference Proceeding
Moradpoor, N., Parr, G., McClean, S., & Scotney, B. (2013). A mathematical model for a GA-based dynamic excess bandwidth allocation algorithm for hybrid PON and wireless technology integrations for next generation broadband access networks. In 2013 5th Proceedings of the Computer Science and Electronic Engineering Conference (CEEC 2013). https://doi.org/10.1109/ceec.2013.6659439

Optical and wireless integration scheme merges the high-speed and high-capacity of the optical networks with the low-cost, wide-coverage and mobility features of the wireless counterparts for the Subscriber Stations (SSs). It is also financially viab... Read More about A mathematical model for a GA-based dynamic excess bandwidth allocation algorithm for hybrid PON and wireless technology integrations for next generation broadband access networks.

An Inter-channel and Intra-channel Dynamic Wavelength/Bandwidth Allocation Algorithm for Integrated Hybrid PON with Wireless Technologies for Next Generation Broadband Access Networks (2013)
Conference Proceeding
Moradpoor, N., Parr, G., Mcclean, S., & Scotney, B. (2013). An Inter-channel and Intra-channel Dynamic Wavelength/Bandwidth Allocation Algorithm for Integrated Hybrid PON with Wireless Technologies for Next Generation Broadband Access Networks. In AFIN 2013 (9-14)

Optical and wireless technology integration schemes merge the high-speed and high-capacity of the optical networks with the low-cost, wide-coverage and mobility features of wireless counterparts for Subscriber Stations (SSs). It is also financially v... Read More about An Inter-channel and Intra-channel Dynamic Wavelength/Bandwidth Allocation Algorithm for Integrated Hybrid PON with Wireless Technologies for Next Generation Broadband Access Networks.

IIDWBA algorithm for integrated hybrid PON with wireless technologies for next generation broadband access networks (2013)
Journal Article
Moradpoor, N., Parr, G., McClean, S., & Scotney, B. (2013). IIDWBA algorithm for integrated hybrid PON with wireless technologies for next generation broadband access networks. Optical Switching and Networking, 10(4), 439-457. https://doi.org/10.1016/j.osn.2013.08.003

Optical and wireless technology integration has been proposed as one of the most promising nominees for the next-generation broadband access networks for quite some time. Integration scheme merges the high-speed and high-capacity of the optical netwo... Read More about IIDWBA algorithm for integrated hybrid PON with wireless technologies for next generation broadband access networks.

Interleaved Polling with Adaptive Cycle Time (IPACT) Implementations Using OPNET (2011)
Conference Proceeding
Moradpoor‫, N., Parr, G., Mcclean, S., Scotney, B., & Owusu, G. (2011). Interleaved Polling with Adaptive Cycle Time (IPACT) Implementations Using OPNET.

The Ethernet Passive Optical Network (EPON) has been considered as one of the most promising candidates for the nextgeneration optical access solutions. In EPON, which is also referred as the Time-Division-Multiplexed PON, upstream fibre is share... Read More about Interleaved Polling with Adaptive Cycle Time (IPACT) Implementations Using OPNET.

Hybrid optical and wireless technology integrations for next generation broadband access networks (2011)
Conference Proceeding
Owusu, G., Moradpoor, N., Parr, G., McClean, S., & Scotney, B. (2011). Hybrid optical and wireless technology integrations for next generation broadband access networks. In 2011 IFIP/IEEE International Symposium on Integrated Network Management (IM 2011). https://doi.org/10.1109/inm.2011.5990515

Hybrid optical and wireless technology integrations have been considered as one of the most promising candidates for the next generation broadband access networks for quite some time. The integration scheme provides the bandwidth advantages of the op... Read More about Hybrid optical and wireless technology integrations for next generation broadband access networks.

Simulation and Performance Evaluation of Bandwidth Allocation Algorithms for Ethernet Passive Optical Networks (EPONs) (2010)
Presentation / Conference
Moradpoor, N., Parr, G., Mcclean, S., Scotney, B., Sivalingam, K., & Madras, I. (2010, December). Simulation and Performance Evaluation of Bandwidth Allocation Algorithms for Ethernet Passive Optical Networks (EPONs). Paper presented at OPNETWORK 2010

Ethernet Passive Optical Network (EPON) has been considered for access networks for quite some time to provide high-speed and high-capacity services. As a novel type of network, EPON presents many challenges so one main aim of this paper is to provid... Read More about Simulation and Performance Evaluation of Bandwidth Allocation Algorithms for Ethernet Passive Optical Networks (EPONs).

Real-Time Data Analytics in Support of Network Resource Management Protocols (2009)
Conference Proceeding
Moradpoor‫, N., Parr, G., Mcclean, S., Scotney, B., & Owusu, G. (2009). Real-Time Data Analytics in Support of Network Resource Management Protocols. In Proceedings of 10th PGNET

Communications Networks Resource Management (RM) functions such as dynamic and static resource usage monitoring, real time resource reservation as well as advance resource reservation have been widely studied in the past few years. Research has been... Read More about Real-Time Data Analytics in Support of Network Resource Management Protocols.