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Designing usable and secure software with IRIS and CAIRIS. (2018)
Book
FAILY, S. 2018. Designing usable and secure software with IRIS and CAIRIS. Cham: Springer [online]. Available from: https://doi.org/10.1007/978-3-319-75493-2

Everyone expects the products and services they use to be secure, but 'building security in' at the earliest stages of a system's design also means designing for use as well. Software that is unusable to end-users and unwieldy to developers and admin... Read More about Designing usable and secure software with IRIS and CAIRIS..

Rationalising decision-making about risk: a normative approach. (2018)
Conference Proceeding
M'MANGA, A., FAILY, S., MCALANEY, J. and WILLIAMS, C. 2018. Rationalising decision-making about risk: a normative approach. In Clarke, N.L. and Furnell, S.M. (eds.) Proceedings of the 12th International symposium on human aspects of information security and assurance (HAISA 2018), 29-31 August 2018, Dundee, UK. Plymouth: University of Plymouth, pages 263-271. Hosted on the CSCAN Archive [online]. Available from: https://www.cscan.org/?page=openaccess&eid=20&id=395

Techniques for determining and applying security decisions typically follow risk-based analytical approaches where alternative options are put forward and weighed in accordance to risk severity metrics based on goals and context. The reasoning or val... Read More about Rationalising decision-making about risk: a normative approach..

Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. (2018)
Journal Article
OCHEI, L.C., BASS, J.M. and PETROVSKI, A. 2018. Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. Journal of cloud computing [online], 7, article ID 22. Available from: https://doi.org/10.1186/s13677-018-0121-8

A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and architects must achieve an o... Read More about Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis..

X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. (2018)
Journal Article
AL-KADRI, M.O., AIJAZ, A. and NALLANATHAN, A. 2019. X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. IEEE wireless communications [online], 26(2), pages 70-77. Available from: https://doi.org/10.1109/MWC.2017.1700243

The recent developments in self-interference (SI) cancellation techniques have led to the practical realization of FD radios that can perform simultaneous transmission and reception. FD technology is attractive for various legacy communications stand... Read More about X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks..

Feature trade-off analysis for reconnaissance detection. (2018)
Book Chapter
KALUTARAGE, H.K. and SHAIKH, S.A. 2018. Feature trade-off analysis for reconnaissance detection. In Heard, N., Adams, N., Rubin-Delanchy, P. and Turcotte, M. (eds.) Data science for cyber security. Security science and technology, 3. London: World Scientific [online], chapter 5, pages 95-126. Available from: https://doi.org/10.1142/9781786345646_005

An effective cyber early warning system (CEWS) should pick up threat activity at an early stage, with an emphasis on establishing hypotheses and predictions as well as generating alerts on (unclassified) situations based on preliminary indications. T... Read More about Feature trade-off analysis for reconnaissance detection..

Real-time relative permeability prediction using deep learning. (2018)
Journal Article
ARIGBE, O.D., OYENEYIN, M.B., ARANA, I. and GHAZI, M.D. 2019. Real-time relative permeability prediction using deep learning. Journal of petroleum exploration and production technologies [online], 9(2), pages 1271-1284. Available from: https://doi.org/10.1007/s13202-018-0578-5

A review of the existing two and three phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real time for different reservoir... Read More about Real-time relative permeability prediction using deep learning..

A holistic metric approach to solving the dynamic location-allocation problem. (2018)
Conference Proceeding
ANKRAH, R., LACROIX, B., MCCALL, J., HARDWICK, A. and CONWAY, A. 2018. A holistic metric approach to solving the dynamic location-allocation problem. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 433-439. Available from: https://doi.org/10.1007/978-3-030-04191-5_35

In this paper, we introduce a dynamic variant of the Location-Allocation problem: Dynamic Location-Allocation Problem (DULAP). DULAP involves the location of facilities to service a set of customer demands over a defined horizon. To evaluate a soluti... Read More about A holistic metric approach to solving the dynamic location-allocation problem..

Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. (2018)
Conference Proceeding
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 357-371. Available from: https://doi.org/10.1007/978-3-030-04191-5_30

Aspect-level sentiment analysis of customer feedback data when done accurately can be leveraged to understand strong and weak performance points of businesses and services and also formulate critical action steps to improve their performance. In this... Read More about Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge..

GramError: a quality metric for machine generated songs. (2018)
Conference Proceeding
DAVIES, C., WIRATUNGA, N. and MARTIN, K. 2018. GramError: a quality metric for machine generated songs. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXV: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in computer science, 11311. Cham: Springer [online], pages 184-190. Available from: https://doi.org/10.1007/978-3-030-04191-5_16

This paper explores whether a simple grammar-based metric can accurately predict human opinion of machine-generated song lyrics quality. The proposed metric considers the percentage of words written in natural English and the number of grammatical er... Read More about GramError: a quality metric for machine generated songs..

Risk information recommendation for engineering workers. (2018)
Conference Proceeding
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2018. Risk information recommendation for engineering workers. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXV: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in computer science, 11311. Cham: Springer [online], pages 311-325. Available from: https://doi.org/10.1007/978-3-030-04191-5_27

Within any sufficiently expertise-reliant and work-driven domain there is a requirement to understand the similarities between specific work tasks. Though mechanisms to develop similarity models for these areas do exist, in practice they have been cr... Read More about Risk information recommendation for engineering workers..

Informed pair selection for self-paced metric learning in Siamese neural networks. (2018)
Conference Proceeding
MARTIN, K., WIRATUNGA, N., MASSIE, S. and CLOS, J. 2018. Informed pair selection for self-paced metric learning in Siamese neural networks. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXV: proceedings of the 38th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) International conference on innovative techniques and applications of artificial intelligence (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in computer science, 11311. Cham: Springer [online], pages 34-49. Available from: https://doi.org/10.1007/978-3-030-04191-5_3

Siamese Neural Networks (SNNs) are deep metric learners that use paired instance comparisons to learn similarity. The neural feature maps learnt in this way provide useful representations for classification tasks. Learning in SNNs is not reliant on e... Read More about Informed pair selection for self-paced metric learning in Siamese neural networks..

Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). (2018)
Journal Article
ANI, M., OLUYEMI, G., PETROVSKI, A. and REZAEI-GOMARI, S. 2019. Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). Journal of petroleum science and engineering [online], 174, pages 833-843. Available from: https://doi.org/10.1016/j.petrol.2018.11.024

The selection of an optimal model from a set of multiple realizations for dynamic reservoir modelling and production forecasts has been a persistent issue for reservoir modelers and decision makers. Current evidence has shown that many presumably goo... Read More about Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP)..

Overlap-based undersampling for improving imbalanced data classification. (2018)
Conference Proceeding
VUTTIPITTAYAMONGKOL, P., ELYAN, E., PETROVSKI, A. and JAYNE, C. 2018. Overlap-based undersampling for improving imbalanced data classification. In Yin, H., Camacho, D., Novais, P. and Tallón-Ballesteros, A. (eds.) Intelligent data engineering and automated learning: proceedings of the 19th International intelligent data engineering and automated learning conference (IDEAL 2018), 21-23 November 2018, Madrid, Spain. Lecture notes in computer science, 11341. Cham: Springer [online], pages 689-697. Available from: https://doi.org/10.1007/978-3-030-03493-1_72

Classification of imbalanced data remains an important field in machine learning. Several methods have been proposed to address the class imbalance problem including data resampling, adaptive learning and cost adjusting algorithms. Data resampling me... Read More about Overlap-based undersampling for improving imbalanced data classification..

Translating contextual integrity into practice using CLIFOD. (2018)
Presentation / Conference
HENRIKSEN-BULMER, J., FAILY, S. and KATOS, V. 2018. Translating contextual integrity into practice using CLIFOD. Presented at the 2018 Networked privacy workshop: privacy in context: critically engaging with theory to guide privacy research and design, part of the 21st ACM conference on computer-supported cooperative work and social computing (CSCW 2018), 3 November 2018, Jersey City, USA.

Public open data increases transparency, but raises questions about the privacy implications of affected individuals. We present a case for using CLIFOD (ContextuaL Integrity for Open Data), a step-by-step privacy decision framework derived from cont... Read More about Translating contextual integrity into practice using CLIFOD..

Assessing system of systems security risk and requirements with OASoSIS. (2018)
Conference Proceeding
KI-ARIES, D., FAILY, S., DOGAN, H. and WILLIAMS, C. 2018. Assessing system of systems security risk and requirements with OASoSIS. In Beckers, K., Faily, S., Lee, S.-W. and Mead, N. (eds.) Proceedings of the 5th International workshop on evolving security and privacy requirements engineering (ESPRE 2018), 20 August 2018, Banff, Canada. Los Alamitos: IEEE Computer Society [online], pages 14-20. Available from: https://doi.org/10.1109/ESPRE.2018.00009

When independent systems come together as a System of Systems (SoS) to achieve a new purpose, dealing with requirements conflicts across systems becomes a challenge. Moreover, assessing and modelling security risk for independent systems and the SoS... Read More about Assessing system of systems security risk and requirements with OASoSIS..

Tool-supporting data protection impact assessments with CAIRIS. (2018)
Conference Proceeding
COLES, J., FAILY, S. and KI-ARIES, D. 2018. Tool-supporting data protection impact assessments with CAIRIS. In Beckers, K., Faily, S., Lee, S.-W. and Mead, N. (eds.) Proceedings of the 5th International workshop on evolving security and privacy requirements engineering (ESPRE 2018), 20 August 2018, Banff, Canada. Los Alamitos: IEEE Computer Society [online], pages 21-27. Available from: https://doi.org/10.1109/ESPRE.2018.00010

The General Data Protection Regulation (GDPR) encourages the use of Data Protection Impact Assessments (DPIAs) to integrate privacy into organisations' activities and practices from early design onwards. To date, however, there has been little prescr... Read More about Tool-supporting data protection impact assessments with CAIRIS..

Emotion-aware polarity lexicons for Twitter sentiment analysis. (2018)
Journal Article
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and P, D. 2021. Emotion-aware polarity lexicons for Twitter sentiment analysis. Expert systems [online], 38(7): artificial intelligence/EDMA 2017, article e12332. Available from: https://doi.org/10.1111/exsy.12332

Theoretical frameworks in psychology map the relationships between emotions and sentiments. In this paper we study the role of such mapping for computational emotion detection from text (e.g. social media) with a aim to understand the usefulness of a... Read More about Emotion-aware polarity lexicons for Twitter sentiment analysis..

Improving kNN for human activity recognition with privileged learning using translation models. (2018)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., SANI, S., MASSIE, S. and COOPER, K. 2018. Improving kNN for human activity recognition with privileged learning using translation models. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 448-463. Available from: https://doi.org/10.1007/978-3-030-01081-2_30

Multiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is preferred by consumers as it is more convenient and less intrusive. This presents a challenge to researchers, as... Read More about Improving kNN for human activity recognition with privileged learning using translation models..

FITsense: employing multi-modal sensors in smart homes to predict falls. (2018)
Conference Proceeding
MASSIE, S., FORBES, G., CRAW, S., FRASER, L. and HAMILTON, G. 2018. FITsense: employing multi-modal sensors in smart homes to predict falls. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 249-263. Available from: https://doi.org/10.1007/978-3-030-01081-2_17

As people live longer, the increasing average age of the population places additional strains on our health and social services. There are widely recognised benefits to both the individual and society from supporting people to live independently for... Read More about FITsense: employing multi-modal sensors in smart homes to predict falls..

Case based reasoning as a model for cognitive artificial intelligence. (2018)
Conference Proceeding
CRAW, S. and AAMODT, A. 2018. Case based reasoning as a model for cognitive artificial intelligence. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 62-77. Available from: https://doi.org/10.1007/978-3-030-01081-2_5

Cognitive Systems understand the world through learning and experience. Case Based Reasoning (CBR) systems naturally capture knowledge as experiences in memory and they are able to learn new experiences to retain in their memory. CBR's retrieve and r... Read More about Case based reasoning as a model for cognitive artificial intelligence..