Detection of Algorithmically Generated Malicious Domain (2018)
Presentation / Conference Contribution
Agyepong, E., Buchanan, W., & Jones, K. (2018, May). Detection of Algorithmically Generated Malicious Domain. Presented at Computer Science & Information Technology

In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, D... Read More about Detection of Algorithmically Generated Malicious Domain.

Detection and prevention of Black Hole Attacks in IOT & WSN (2018)
Presentation / Conference Contribution
Ali, S., Khan, M. A., Ahmad, J., Malik, A. W., & ur Rehman, A. (2018, April). Detection and prevention of Black Hole Attacks in IOT & WSN. Presented at 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC), Barcelona, Spain

Wireless Sensor Network is the combination of small devices called sensor nodes, gateways and software. These nodes use wireless medium for transmission and are capable to sense and transmit the data to other nodes. Generally, WSN composed of two typ... Read More about Detection and prevention of Black Hole Attacks in IOT & WSN.

Analysis: Building the Future of EU: Moving Forward with International Collaboration on Blockchain (2018)
Journal Article
Buchanan, B., & Naqvi, N. (2018). Analysis: Building the Future of EU: Moving Forward with International Collaboration on Blockchain. The Journal of the British Blockchain Association, 1(1), 1-4

A blockchain enabled 'Digital Single Economy " can act as a catalyst for growth and could provide a platform where borderless innovative practices will thrive and create a true collaborative global economy, with shared goals and objectives for the be... Read More about Analysis: Building the Future of EU: Moving Forward with International Collaboration on Blockchain.

Forensics study of IMO call and chat app. (2018)
Journal Article
Sudozai, M., Saleem, S., Buchanan, W. J., Habib, N., & Zia, H. (2018). Forensics study of IMO call and chat app. Digital Investigation, https://doi.org/10.1016/j.diin.2018.04.006

Smart phones often leave behind a wealth of information that can be used as an evidence during an investigation. There are thus many smart phone applications that employ encryption to store and/or transmit data, and this can add a layer of complexity... Read More about Forensics study of IMO call and chat app..

Improving User Confidence in Concept Maps: Exploring Data Driven Explanations (2018)
Presentation / Conference Contribution
Le Bras, P., Robb, D. A., Methven, T. S., Padilla, S., & Chantler, M. J. (2018, April). Improving User Confidence in Concept Maps: Exploring Data Driven Explanations. Presented at 2018 ACM CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada

Automated tools are increasingly being used to generate highly engaging concept maps as an aid to strategic planning and other decision-making tasks. Unless stakeholders can understand the principles of the underlying layout process, however, we have... Read More about Improving User Confidence in Concept Maps: Exploring Data Driven Explanations.

Machine learning and semantic analysis of in-game chat for cyber bullying (2018)
Journal Article
Murnion, S., Buchanan, W. J., Smales, A., & Russell, G. (2018). Machine learning and semantic analysis of in-game chat for cyber bullying. Computers and Security, 76, 197-213. https://doi.org/10.1016/j.cose.2018.02.016

One major problem with cyberbullying research is the lack of data, since researchers are traditionally forced to rely on survey data where victims and perpetrators self-report their impressions. In this paper, an automatic data collection system is p... Read More about Machine learning and semantic analysis of in-game chat for cyber bullying.

Lightweight cryptography methods (2018)
Journal Article
Buchanan, W. J., Li, S., & Asif, R. (2018). Lightweight cryptography methods. Journal of Cyber Security Technology, 1(3-4), 187-201. https://doi.org/10.1080/23742917.2017.1384917

While our conventional cryptography methods, such for AES (encryption), SHA-256 (hashing) and RSA/Elliptic Curve (signing), work well on systems which have reasonable processing power and memory capabilities, these do not scale well into a world with... Read More about Lightweight cryptography methods.

Security Risk Assessment of Critical Infrastructure Systems: A Comparative Study (2018)
Journal Article
Tweneboah-Koduah, S., & Buchanan, W. J. (2018). Security Risk Assessment of Critical Infrastructure Systems: A Comparative Study. Computer Journal, 61(9), 1389-1406. https://doi.org/10.1093/comjnl/bxy002

Recent cyberattacks on critical infrastructure systems coupled with the technology-induced complexity of the system of systems have necessitated a review of existing methods of assessing critical systems security risk exposure. The question is; do ex... Read More about Security Risk Assessment of Critical Infrastructure Systems: A Comparative Study.

A Trust-based Intrusion Detection System for Mobile RPL Based Networks (2018)
Presentation / Conference Contribution
Faiza, M., Tandjaoui, D., Romdhani, I., & Nabil, D. (2017, June). A Trust-based Intrusion Detection System for Mobile RPL Based Networks. Presented at 10th IEEE International Conference on Internet of Things (iThings-2017)

Successful deployment of Low power and Lossy Networks (LLNs) requires self-organising, self-configuring, security, and mobility support. However, these characteristics can be exploited to perform security attacks against the Routing Protocol for Low-... Read More about A Trust-based Intrusion Detection System for Mobile RPL Based Networks.

Distance Measurement Methods for Improved Insider Threat Detection (2018)
Journal Article
Lo, O., Buchanan, W. J., Griffiths, P., & Macfarlane, R. (2018). Distance Measurement Methods for Improved Insider Threat Detection. Security and Communication Networks, 2018, 1-18. https://doi.org/10.1155/2018/5906368

Insider threats are a considerable problem within cyber security and it is often difficult to detect these threats using signature detection. Increasing machine learning can provide a solution, but these methods often fail to take into account change... Read More about Distance Measurement Methods for Improved Insider Threat Detection.

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.

Mining malware command and control traces (2018)
Presentation / Conference Contribution
McLaren, P., Russell, G., & Buchanan, B. (2017, July). Mining malware command and control traces. Presented at 2017 Computing Conference

Detecting botnets and advanced persistent threats is a major challenge for network administrators. An important component of such malware is the command and control channel, which enables the malware to respond to controller commands. The detection o... Read More about Mining malware command and control traces.