Outputs (20)

Decentralised Privacy: A Distributed Ledger Approach (2021)
Book Chapter
Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). Decentralised Privacy: A Distributed Ledger Approach. In C. Mustansar Hussain, & P. Di Sia (Eds.), Handbook of Smart Materials, Technologies, and Devices (1-26). Springer. https://doi.org/10.1007/978-3-030-58675-1_58-1

Our world due to the technological progress became fast-paced and is constantly evolving, thus changing every single day. Consequently, the most valuable asset on earth is not gold or oil anymore but data. Big data companies try to take advantage of... Read More about Decentralised Privacy: A Distributed Ledger Approach.

Developing Visualisations to Enhance an Insider Threat Product: A Case Study (2021)
Presentation / Conference Contribution
Graham, M. (2021, October). Developing Visualisations to Enhance an Insider Threat Product: A Case Study. Presented at 18th IEEE Symposium on Visualization for Cyber Security, New Orleans, USA [Online]

This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily spot the... Read More about Developing Visualisations to Enhance an Insider Threat Product: A Case Study.

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT (2021)
Journal Article
Almas Khan, M., Khan, M. A., Ullah Jan, S., Ahmad, J., Jamal, S. S., Shah, A. A., Pitropakis, N., Buchanan, W. J., Alonistioti, N., Panagiotakis, S., & Markakis, E. K. (2021). A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT. Sensors, 21(21), Article 7016. https://doi.org/10.3390/s21217016

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish–subscribe-based protocol for the communication of sensor or ev... Read More about A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

A Blockchain Framework in Post-Quantum Decentralization (2021)
Journal Article
Saha, R., Kumar, G., Devgun, T., Buchanan, W., Thomas, R., Alazab, M., Kim, T.-H., & Rodrigues, J. (2023). A Blockchain Framework in Post-Quantum Decentralization. IEEE Transactions on Services Computing, 16(1), https://doi.org/10.1109/tsc.2021.3116896

The decentralization and transparency have provided wide acceptance of blockchain technology in various sectors through numerous applications. The claimed security services by blockchain have been proved using various cryptographic techniques, mainly... Read More about A Blockchain Framework in Post-Quantum Decentralization.

A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions (2021)
Journal Article
Saha, R., Geetha, G., Kumar, G., Buchanan, W. J., & Kim, T. (2021). A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions. Applied Sciences, 11(17), Article 8073. https://doi.org/10.3390/app11178073

Cryptographic algorithms and functions should possess some of the important functional requirements such as: non-linearity, resiliency, propagation and immunity. Several previous studies were executed to analyze these characteristics of the cryptogra... Read More about A Secure Random Number Generator with Immunity and Propagation Characteristics for Cryptography Functions.

LiSP-XK: Extended Light-Weight Signcryption for IoT in Resource-Constrained Environments (2021)
Journal Article
Kim, T.-H., Kumar, G., Saha, R., Buchanan, W. J., Devgun, T., & Thomas, R. (2021). LiSP-XK: Extended Light-Weight Signcryption for IoT in Resource-Constrained Environments. IEEE Access, 9, 100972-100980. https://doi.org/10.1109/access.2021.3097267

There is an increasing drive to provide improved levels of trust within an Internet-of-Things (IoTs) environments, but the devices and sensors used tend to be limited in their capabilities for dealing with traditional cryptography methods. Resource c... Read More about LiSP-XK: Extended Light-Weight Signcryption for IoT in Resource-Constrained Environments.

Blockchain for edge-enabled smart cities applications (2021)
Journal Article
Jan, M. A., Yeh, K.-H., Tan, Z., & Wu, Y. (2021). Blockchain for edge-enabled smart cities applications. Journal of Information Security and Applications, 61, 102937. https://doi.org/10.1016/j.jisa.2021.102937

The Internet of Things (IoT)-enabled devices are increasing at an exponential rate and share massive data generated in smart cities around the globe. The time-critical and delay-sensitive nature of this data means that cloud service providers are una... Read More about Blockchain for edge-enabled smart cities applications.

PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform (2021)
Journal Article
Abramson, W., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform. Software Impacts, 9, Article 100101. https://doi.org/10.1016/j.simpa.2021.100101

PyDentity lowers the entry barrier for parties interested in experimenting with the Hyperledger’s verifiable information exchange platform. It enables educators, developers and researchers to configure and initialise a set of actors easily as associa... Read More about PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform.

Differential Area Analysis for Ransomware Attack Detection within Mixed File Datasets (2021)
Journal Article
Davies, S. R., Macfarlane, R., & Buchanan, W. J. (2021). Differential Area Analysis for Ransomware Attack Detection within Mixed File Datasets. Computers and Security, 108, Article 102377. https://doi.org/10.1016/j.cose.2021.102377

The threat from ransomware continues to grow both in the number of affected victims as well as the cost incurred by the people and organisations impacted in a successful attack. In the majority of cases, once a victim has been attacked there remain o... Read More about Differential Area Analysis for Ransomware Attack Detection within Mixed File Datasets.

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  .

An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples (2021)
Presentation / Conference Contribution
Verdi, M., Sami, A., Akhondali, J., Khomh, F., Uddin, G., & Karami Motlagh, A. (2021, May). An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. Presented at 43rd International Conference on Software Engineering, Online

Software developers share programming solutions in Q&A sites like Stack Overflow, Stack Exchange, Android forum, and so on. The reuse of crowd-sourced code snippets can facilitate rapid prototyping. However, recent research shows that the shared code... Read More about An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples.

Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks (2021)
Journal Article
Khalafi, Z. S., Dehghani, M., Khalili, A., Sami, A., Vafamand, N., & Dragicevic, T. (2022). Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks. IEEE Transactions on Industrial Electronics, 69(5), 4697-4706. https://doi.org/10.1109/tie.2021.3080212

Accurate state estimation is essential for correct supervision of power grids. With the existence of cyber-attacks, state estimation may become inaccurate, which can eventually lead to wrong supervisory decision making. To detect cyber-attacks in pow... Read More about Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks.

PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN (2021)
Presentation / Conference Contribution
Romanini, D., Hall, A. J., Papadopoulos, P., Titcombe, T., Ismail, A., Cebere, T., Sandmann, R., Roehm, R., & Hoeh, M. A. (2021, May). PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN. Poster presented at ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML 2021), Online

We introduce PyVertical, a framework supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist to train neural networks on data features vertically partitioned across multiple owners while keep... Read More about PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN.

Practical defences against model inversion attacks for split neural networks (2021)
Presentation / Conference Contribution
Titcombe, T., Hall, A. J., Papadopoulos, P., & Romanini, D. (2021, May). Practical defences against model inversion attacks for split neural networks. Paper presented at ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML 2021), Online

We describe a threat model under which a split network-based federated learning system is susceptible to a model inversion attack by a malicious computational server. We demonstrate that the attack can be successfully performed with limited knowledge... Read More about Practical defences against model inversion attacks for split neural networks.

Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT (2021)
Journal Article
Papadopoulos, P., Thornewill Von Essen, O., Pitropakis, N., Chrysoulas, C., Mylonas, A., & Buchanan, W. J. (2021). Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT. Journal of Cybersecurity and Privacy, 1(2), 252-273. https://doi.org/10.3390/jcp1020014

As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially. Technology is shifting towards a profit-driven Internet of Things market where security is an afterthought. Traditional defe... Read More about Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT.

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.

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.

The reality of 'cyber security awareness': findings and policy implications for Scotland (2021)
Report
Horgan, S. (2021). The reality of 'cyber security awareness': findings and policy implications for Scotland. Scottish Centre for Crime and Justice Research, the Scottish Institute for Policing Research, and the Scottish Government

This briefing paper represents a summary of doctoral research that explores how different groups make sense of and respond to cybercrime in their everyday lives. The research found that people from different groups, places, and times think about cybe... Read More about The reality of 'cyber security awareness': findings and policy implications for Scotland.

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.