Outputs (701)

Fault-tolerant AI-driven Intrusion Detection System for the Internet of Things (2021)
Journal Article
Medjek, F., Tandjaoui, D., Djedjig, N., & Romdhani, I. (2021). Fault-tolerant AI-driven Intrusion Detection System for the Internet of Things. International Journal of Critical Infrastructure Protection, 34, Article 100436. https://doi.org/10.1016/j.ijcip.2021.100436

Internet of Things (IoT) has emerged as a key component of all advanced critical infrastructures. However, with the challenging nature of IoT, new security breaches have been introduced, especially against the Routing Protocol for Low-power and Lossy... Read More about Fault-tolerant AI-driven Intrusion Detection System for the Internet of Things.

A Comparative Analysis of Honeypots on Different Cloud Platforms (2021)
Journal Article
Kelly, C., Pitropakis, N., Mylonas, A., McKeown, S., & Buchanan, W. J. (2021). A Comparative Analysis of Honeypots on Different Cloud Platforms. Sensors, 21(7), Article 2433. https://doi.org/10.3390/s21072433

In 2019, the majority of companies used at least one cloud computing service and it is expected that by the end of 2021, cloud data centres will process 94% of workloads. The financial and operational advantages of moving IT infrastructure to special... Read More about A Comparative Analysis of Honeypots on Different Cloud Platforms.

Privacy and Trust Redefined in Federated Machine Learning (2021)
Journal Article
Papadopoulos, P., Abramson, W., Hall, A. J., Pitropakis, N., & Buchanan, W. J. (2021). Privacy and Trust Redefined in Federated Machine Learning. Machine Learning and Knowledge Extraction, 3(2), 333-356. https://doi.org/10.3390/make3020017

A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited... Read More about Privacy and Trust Redefined in Federated Machine Learning.

A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node (2021)
Journal Article
Thomson, C., Wadhaj, I., Tan, Z., & Al-Dubai, A. (2021). A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node. Wireless Networks, 27(5), 3423-3439. https://doi.org/10.1007/s11276-021-02580-8

Utilising the mobilisation of a sink node in a wireless sensor network to combat the energy hole, or hotspot issue, is well referenced. However, another issue , that of energy spikes may remain. With the mobile sink node potentially communicating wit... Read More about A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node.

Machine Learning-driven Optimization for SVM-based Intrusion Detection System in Vehicular Ad Hoc Networks (2021)
Journal Article
Alsarhan, A., Alauthman, M., Alshdaifat, E., Al-Ghuwairi, A.-R., & Al-Dubai, A. (2023). Machine Learning-driven Optimization for SVM-based Intrusion Detection System in Vehicular Ad Hoc Networks. Journal of Ambient Intelligence and Humanized Computing, 14(5), 6113-6122. https://doi.org/10.1007/s12652-021-02963-x

Machine Learning (ML) driven solutions have been widely used to secure wireless communications Vehicular ad hoc networks (VANETs) in recent studies. Unlike existing works, this paper applies support vector machine (SVM) for intrusion detection in VAN... Read More about Machine Learning-driven Optimization for SVM-based Intrusion Detection System in Vehicular Ad Hoc Networks.

Vehicular Computation Offloading for Industrial Mobile Edge Computing (2021)
Journal Article
Zhao, L., Yang, K., Tan, Z., Song, H., Al-Dubai, A., & Zomaya, A. (2021). Vehicular Computation Offloading for Industrial Mobile Edge Computing. IEEE Transactions on Industrial Informatics, 17(11), 7871-7881. https://doi.org/10.1109/TII.2021.3059640

Due to the limited local computation resource, industrial vehicular computation requires offloading the computation tasks with time-delay sensitive and complex demands to other intelligent devices (IDs) once the data is sensed and collected collabora... Read More about Vehicular Computation Offloading for Industrial Mobile Edge Computing.

A Novel Heuristic Data Routing for Urban Vehicular Ad-hoc Networks (2021)
Journal Article
Hawbani, A., Wang, X., Al-Dubai, A., Zhao, L., Busaileh, . O., Liu, P., & Al-qaness, M. (2021). A Novel Heuristic Data Routing for Urban Vehicular Ad-hoc Networks. IEEE Internet of Things Journal, 8(11), 8976-8989. https://doi.org/10.1109/JIOT.2021.3055504

This work is devoted to solving the problem of multi-criteria multi-hop routing in vehicular ad-hoc networks (VANETs), aiming at three goals, increasing the end-to-end delivery ratio, reducing the end-to-end latency, and minimizing the network overhe... Read More about A Novel Heuristic Data Routing for Urban Vehicular Ad-hoc Networks.

Secure Lightweight Stream Data Outsourcing for Internet of Things (2021)
Journal Article
Peng, S., Zhao, L., Al-Dubai, A., Zomaya, A., Hu, J., Min, G., & Wang, Q. (2021). Secure Lightweight Stream Data Outsourcing for Internet of Things. IEEE Internet of Things Journal, 8(13), 10815-10829. https://doi.org/10.1109/JIOT.2021.3050732

The epoch of the Internet of Things (IoT) has come by enabling almost everything to gather and share electronic information. Considering the unreliable factors of public IoT, how to outsource huge amounts of indispensable stream data generated by the... Read More about Secure Lightweight Stream Data Outsourcing for Internet of Things.

An experimental analysis of attack classification using machine learning in IoT networks (2021)
Journal Article
Churcher, A., Ullah, R., Ahmad, J., Ur Rehman, S., Masood, F., Gogate, M., Alqahtani, F., Nour, B., & Buchanan, W. J. (2021). An experimental analysis of attack classification using machine learning in IoT networks. Sensors, 21(2), Article 446. https://doi.org/10.3390/s21020446

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature,... Read More about An experimental analysis of attack classification using machine learning in IoT networks.

Ontology-based Course Teacher Assignment within Universities (2020)
Journal Article
Ashour, G., Al-Dubai, A., & Romdhani, I. (2020). Ontology-based Course Teacher Assignment within Universities. International Journal of Advanced Computer Science and Applications, 11(7), https://doi.org/10.14569/ijacsa.2020.0110787

Educational institutions suffer from the enormous amount of data that keeps growing continuously. These data are usually scattered and unorganised, and it comes from different resources with different formats. Besides, modernization vision within the... Read More about Ontology-based Course Teacher Assignment within Universities.

Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach (2020)
Presentation / Conference Contribution
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020, February). Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. Presented at ICISSP 2020, Valletta, Malta

Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate. Even with adequate training and high situational awareness, it can still be hard for users to continually be awa... Read More about Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach.

Privacy-preserving Surveillance Methods using Homomorphic Encryption (2020)
Presentation / Conference Contribution
Bowditch, W., Abramson, W., Buchanan, W. J., Pitropakis, N., & Hall, A. J. (2020, February). Privacy-preserving Surveillance Methods using Homomorphic Encryption. Presented at 6th International Conference on Information Security Systems and Privacy (ICISSP), Valletta, Malta

Data analysis and machine learning methods often involve the processing of cleartext data, and where this could breach the rights to privacy. Increasingly, we must use encryption to protect all states of the data: in-transit, at-rest, and in-memory.... Read More about Privacy-preserving Surveillance Methods using Homomorphic Encryption.

Novel Online Sequential Learning-Based Adaptive Routing for Edge Software-Defined Vehicular Networks (2020)
Journal Article
Zhao, L., Zhao, W., Hawbani, A., Al-Dubai, A. Y., Min, G., Zomaya, A., & Gong, C. (2021). Novel Online Sequential Learning-Based Adaptive Routing for Edge Software-Defined Vehicular Networks. IEEE Transactions on Wireless Communications, 20(5), 2991-3004. https://doi.org/10.1109/twc.2020.3046275

To provide efficient networking services at the edge of Internet-of-Vehicles (IoV), Software-Defined Vehicular Network (SDVN) has been a promising technology to enable intelligent data exchange without giving additional duties to the resource constra... Read More about Novel Online Sequential Learning-Based Adaptive Routing for Edge Software-Defined Vehicular Networks.

Understanding Personal Online Risk To Individuals Via Ontology Development (2020)
Presentation / Conference Contribution
Haynes, D. (2020, July). Understanding Personal Online Risk To Individuals Via Ontology Development. Presented at International Societey for Knowledge Organziation (ISKO) 2020, Aalborg, Denmark

The concept of risk is widely misunderstood because of the different contexts in which it is used. This paper describes the development of an ontology of risk as a way of better understanding the nature of the potential harms individuals are exposed... Read More about Understanding Personal Online Risk To Individuals Via Ontology Development.

Stratified Opposition-Based Initialization for Variable-Length Chromosome Shortest Path Problem Evolutionary Algorithms (2020)
Journal Article
Ghanami, A., Li, . J., Hawbani, A., & Al-Dubai, A. (2021). Stratified Opposition-Based Initialization for Variable-Length Chromosome Shortest Path Problem Evolutionary Algorithms. Expert Systems with Applications, 170, Article 114525. https://doi.org/10.1016/j.eswa.2020.114525

Initialization is the first and a major step in the implementation of evolutionary algorithms (EAs). Although there are many common general methods to initialize EAs such as the pseudo-random number generator (PRNG), there is no single method that ca... Read More about Stratified Opposition-Based Initialization for Variable-Length Chromosome Shortest Path Problem Evolutionary Algorithms.

Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing (2020)
Journal Article
Buchanan, W. J., Imran, M. A., Ur-Rehman, M., Zhang, L., Abbasi, Q. H., Chrysoulas, C., Haynes, D., Pitropakis, N., & Papadopoulos, P. (2020). Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing. Frontiers in Communications and Networks, https://doi.org/10.3389/frcmn.2020.583376

The outbreak of viruses have necessitated contact tracing and infection tracking methods. Despite various efforts, there is currently no standard scheme for the tracing and tracking. Many nations of the world have therefore, developed their own ways... Read More about Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing.

PoNW: A Secure and Scalable Proof-of-Notarized-Work Based Consensus Mechanism (2020)
Presentation / Conference Contribution
Abubakar, M., Jaroucheh, Z., Al-Dubai, A., & Buchanan, W. (2020, December). PoNW: A Secure and Scalable Proof-of-Notarized-Work Based Consensus Mechanism. Presented at ICVISP 2020: The 2020 4th International Conference on Vision, Image and Signal Processing, Bangkok

The original consensus algorithm-Proof of Work (PoW) has been widely utilized in the blockchain systems and is been adopted by many cryptocurrencies, such as Bitcoin and Ethereum, among many others. Nevertheless, the concept has received criticisms o... Read More about PoNW: A Secure and Scalable Proof-of-Notarized-Work Based Consensus Mechanism.

A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric (2020)
Journal Article
Stamatellis, C., Papadopoulos, P., Pitropakis, N., Katsikas, S., & Buchanan, W. J. (2020). A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric. Sensors, 20(22), Article 6587. https://doi.org/10.3390/s20226587

Electronic health record (EHR) management systems require the adoption of effective technologies when health information is being exchanged. Current management approaches often face risks that may expose medical record storage solutions to common sec... Read More about A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric.

A Novel Web Attack Detection System for Internet of Things via Ensemble Classification (2020)
Journal Article
Luo, C., Tan, Z., Min, G., Gan, J., Shi, W., & Tian, Z. (2021). A Novel Web Attack Detection System for Internet of Things via Ensemble Classification. IEEE Transactions on Industrial Informatics, 17(8), 5810-5818. https://doi.org/10.1109/tii.2020.3038761

Internet of things (IoT) has become one of the fastestgrowing technologies and has been broadly applied in various fields. IoT networks contain millions of devices with the capability of interacting with each other and providing functionalities that... Read More about A Novel Web Attack Detection System for Internet of Things via Ensemble Classification.

Fast Probabilistic Consensus with Weighted Votes (2020)
Presentation / Conference Contribution
Müller, S., Penzkofer, A., Ku´smierz, B., Camargo, D., & Buchanan, W. J. (2020, November). Fast Probabilistic Consensus with Weighted Votes. Presented at FTC 2020 - Future Technologies Conference 2020, Vancouver, Canada

The fast probabilistic consensus (FPC) is a voting consensus protocol that is robust and efficient in Byzantine infrastructure. We propose an adaption of the FPC to a setting where the voting power is proportional to the nodes reputations. We model t... Read More about Fast Probabilistic Consensus with Weighted Votes.