Outputs (274)

Team Formation Through Preference-Based Behavior Composition (2017)
Presentation / Conference Contribution
Barati, M., & St-Denis, R. (2017). Team Formation Through Preference-Based Behavior Composition. In Multiagent System Technologies: 15th German Conference, MATES 2017, Leipzig, Germany, August 23–26, 2017, Proceedings (54-71). https://doi.org/10.1007/

A team formation problem consists in finding an effective group of experts in a social network to accomplish a job with a minimum expenditure of energy and time. This problem has been transposed into the domain of multiagent systems to form a team of... Read More about Team Formation Through Preference-Based Behavior Composition.

Making and Unfinishedness: Designing Toolkits for Negotiation (2017)
Journal Article
Smyth, M., & Helgason, I. (2017). Making and Unfinishedness: Designing Toolkits for Negotiation. Design Journal, 20(sup1), S3966-S3974. https://doi.org/10.1080/14606925.2017.1352899

The diffusion and democratisation of computing technologies and physical prototyping systems has supported the rise of Do-It-Yourself culture. In the context of design innovation, this shift has undoubtedly blurred the lines between the roles of amat... Read More about Making and Unfinishedness: Designing Toolkits for Negotiation.

A systematic analysis of random forest based social media spam classification (2017)
Presentation / Conference Contribution
Al-Janabi, M., & Andras, P. (2017). A systematic analysis of random forest based social media spam classification. In Network and System Security: 11th International Conference, NSS 2017, Helsinki, Finland, August 21–23, 2017, Proceedings (427-438). ht

Recently random forest classification became a popular choice machine learning applications aimed to detect spam content in online social networks. In this paper, we report a systematic analysis of random forest classification for this purpose. We as... Read More about A systematic analysis of random forest based social media spam classification.

The industrial control system cyber defence triage process (2017)
Journal Article
Cook, A., Janicke, H., Smith, R., & Maglaras, L. (2017). The industrial control system cyber defence triage process. Computers and Security, 70, 467-481. https://doi.org/10.1016/j.cose.2017.07.009

The threat to Industrial Control Systems (ICS) from cyber attacks is widely acknowledged by governments and literature. Operators of ICS are looking to address these threats in an effective and cost-sensitive manner that does not expose their operati... Read More about The industrial control system cyber defence triage process.

SDQ: enabling rapid QoE experimentation using Software Defined Networking (2017)
Presentation / Conference Contribution
Fawcett, L., Mu, M., Broadbent, M., Hart, N., & Race, N. (2017). SDQ: enabling rapid QoE experimentation using Software Defined Networking. In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) (656-659). https://doi.org/10.23919/

The emerging network paradigm of Software Defined Networking (SDN) has been increasingly adopted to improve the Quality of Experiences (QoE) across multiple HTTP adaptive streaming (HAS) instances. However, there is currently a gap between research a... Read More about SDQ: enabling rapid QoE experimentation using Software Defined Networking.

Applied Machine Learning predictive analytics to SQL Injection Attack detection and prevention (2017)
Presentation / Conference Contribution
Uwagbole, S. O., Buchanan, W. J., & Fan, L. (2017). Applied Machine Learning predictive analytics to SQL Injection Attack detection and prevention. In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM),. https://doi.org/10.23919/I

The back-end database is pivotal to the storage of the massive size of big data Internet exchanges stemming from cloud-hosted web applications to Internet of Things (IoT) smart devices. Structured Query Language (SQL) Injection Attack (SQLIA) remains... Read More about Applied Machine Learning predictive analytics to SQL Injection Attack detection and prevention.

Trust-Based Defence Model Against MAC Unfairness Attacks for IoT (2017)
Presentation / Conference Contribution
Djedjig, N., Tandjaoui, D., Romdhani, I., & Medjek, F. (2017). Trust-Based Defence Model Against MAC Unfairness Attacks for IoT. In C. Westphall, K. El-Khatib, D. Krstić, & H. Menouar (Eds.), Proceedings of the Thirteenth International Conference on Wire

The vulnerability of IoT networks makes channel access security a serious problem. The IEEE 802.15.4 MAC (Media Access Control) layer faces the risk of attacks from malicious nodes which attempts to get a dominating position and hold unfair advantage... Read More about Trust-Based Defence Model Against MAC Unfairness Attacks for IoT.

Complex Pleasures: Designing Optional interactions for Public Spaces (2017)
Thesis
Helgason, I. Complex Pleasures: Designing Optional interactions for Public Spaces. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/1022893

This research aims to contribute to knowledge about the design of interactive systems sited in public spaces. In particular, the study concerns "optional interactions" where systems invite interaction from passers-by. These systems are action-orienta... Read More about Complex Pleasures: Designing Optional interactions for Public Spaces.

Information Technology – Next Generation: The Impact of 5G on the Evolution of Health and Care Services (2017)
Presentation / Conference Contribution
Lim, A. K., Thuemmler, C., Paulin, A., Jell, T., & Keow Lim, A. K. (2017). Information Technology – Next Generation: The Impact of 5G on the Evolution of Health and Care Services. In S. Latifi (Ed.), Information Technology-Next Generation (811-817). htt

As more and more details of 5G technology specifications unveil and standards emerge it becomes clear that 5G will have an enabling effect on many different verticals including automotive, mobility and health. This paper gives an overview about techn... Read More about Information Technology – Next Generation: The Impact of 5G on the Evolution of Health and Care Services.

Data-to-Text Generation Improves Decision-Making Under Uncertainty (2017)
Journal Article
Gkatzia, D., Lemon, O., & Rieser, V. (2017). Data-to-Text Generation Improves Decision-Making Under Uncertainty. IEEE Computational Intelligence Magazine, 12(3), 10-17. https://doi.org/10.1109/MCI.2017.2708998

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. This article presents a comparison of different information presentations for uncertain data and, for the first time, measures their e... Read More about Data-to-Text Generation Improves Decision-Making Under Uncertainty.