Predicting Malicious Insider Threat Scenarios Using Organizational Data and a Heterogeneous Stack-Classifier
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 exis...
Open-source Data Analysis and Machine Learning for Asthma Hospitalisation Rates
Rooney, L., Chute, C., Buchanan, W. J., Smales, A., & Hepburn, L. (2018)
Open-source Data Analysis and Machine Learning for Asthma Hospitalisation Rates. In Proceedings of ThinkMind - GLOBAL HEALTH 2018, The Seventh International Conference on Global Health Challenges
Long-term conditions in Scotland account for 80% of all GP consultations; they also account for 60% of all deaths in Scotland. Asthma and Chronic Obstructive Pulmonary Disease...
Correlation Power Analysis on the PRESENT Block Cipher on an Embedded Device
Lo, O., Buchanan, W. J., & Carson, D. (2018)
Correlation Power Analysis on the PRESENT Block Cipher on an Embedded Device. In ARES 2018 Proceedings of the 13th International Conference on Availability, Reliability and Securityhttps://doi.org/10.1145/3230833.3232801
Traditional cryptographic techniques have proven to work well on most modern computing devices but they are unsuitable for devices (e.g. IoT devices) where memory, power consu...
Insider threat detection using principal component analysis and self-organising map
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 wh...
Secret shares to protect health records in Cloud-based infrastructures
Buchanan, W. J., Ukwandu, E., van Deursen, N., Fan, L., Russell, G., Lo, O., & Thuemmler, C. (2016)
Secret shares to protect health records in Cloud-based infrastructures. In 2015 17th International Conference on E-health Networking, Application & Services (HealthCom)https://doi.org/10.1109/HealthCom.2015.7454589
Increasingly health records are stored in cloud-based systems, and often protected by a private key. Unfortunately the loss of this key can cause large-scale data loss. This p...
RESCUE: Resilient Secret Sharing Cloud-based Architecture.
Ukwandu, E., Buchanan, W. J., Fan, L., Russell, G., & Lo, O. (2015)
RESCUE: Resilient Secret Sharing Cloud-based Architecture. In 2015 IEEE Trustcom/BigDataSE/ISPA Vol. 1, (872-879). https://doi.org/10.1109/Trustcom.2015.459
This paper presents an architecture (RESCUE) of a system that is capable of implementing: a keyless encryption method; self-destruction of data within a time frame without use...
Sticky-Policy enabled authenticated OOXML for Health Care
Spyra, G., Buchanan, W. J., & Ekonomou, E. (2015)
Sticky-Policy enabled authenticated OOXML for Health Care. In Proceedings of BCS Health Informatics Scotland 2015 Conferencehttps://doi.org/10.14236/ewic/HIS2015.3
This paper proposes a secure medical document sharing construction, which addresses confidentiality and authenticity concerns related to cloud-based data protection issues. Th...
Performance analysis of network based forensic systems for in-line and out-of-line detection and logging.
Graves, J., Buchanan, W. J., Saliou, L. & Old, L. J. (2006)
Performance analysis of network based forensic systems for in-line and out-of-line detection and logging. ISBN 1905305206
Network based forensic investigations often rely on data provided by properly configured network- based devices. The logs from interconnected devices such as routers, servers ...
A framework to detect novel computer viruses via system calls.
Abimbola, A., Munoz, J., & Buchanan, W. J. (2005)
A framework to detect novel computer viruses via system calls. In M. Merabti, R. Pereira, & O. Abuelma'atti (Eds.), 7th Annual PG Symposium on The Convergence of Telecommunications, Networking and Broadcasting, 308-313
This paper describes a framework for detecting self-propagating email viruses based on deterministic system calls derived from associated email client’s dynamic link libraries...