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Dr. Edward Apeh is a member of the department of computing and informatics within the Faculty of Science and Technology at Bournemouth University. He has over 15 years industry experience and has led successful projects in the areas of cyber security, data analytics, data mining and web technologies funded by Innovate UK and Great Western Research. The results of his work have been published and down-streamed into other projects and commercial products. He has organized and delivered a number of academic and industry workshops in the areas of data analytics, knowledge management and cyber-security. He has also reviewed for various journals and published in the areas of data analytics, data mining, cognitive computation and neuro-computing; and has a patent in signal analysis and processing. Dr. Edward Apeh received his M. Sc. degree in Intelligent Systems from the University College London in 2003, and his M. Phil. and PhD. degrees in Computational Intelligence in 2009 and 2013 respectively from Bournemouth University, Bournemouth UK.
Dr. Edward Apeh's main research interests include cyber analytics, data mining, machine learning, intelligent systems design, knowledge discovery, adaptive systems, etc.
- Ambore, S., Richardson, C., Dogan, H., Apeh, E. and Osselton, D., 2017. A Resilient Cybersecurity Framework for Mobile Financial Services (MFS). Journal of Cyber Security Technology, 1 (3-4), 202-224.
- Apeh, E., Richardson, C. and Curran, T., 2015. Monitoring Social Media for Cyber-stalking. The Cyber Security Review, Spring 2015, 67-74.
- Apeh, E., Gabrys, B. and Schierz, A., 2014. Customer profile classification: To adapt classifiers or to relabel customer profiles? Neurocomputing, 132, 3-13.
- Apeh, E. and Gabrys, B., 2013. Detecting and Visualizing the Change in Classification of Customer Profiles based on Transactional Data. Evolving Systems, 4 (1), 27-42.
- Apeh, E. and Jeffries, S., 2017. Standard Operating Procedures for Cybercrime Investigations: A Systematic Literature Review. Psychological and Behavioural Examinations in Cybersecurity. IGI.
- Ambore, S., Richardson, C., Apeh, E. and Dogan, H., 2018. Have usability and security trade-offs in mobile financial services become untrustworthy?
- Apeh, E., 2017. Analysis of the Security Implications of Wearable Technology using Socio-technical Perspective. In: The 25th European Conference on Information Systems 5-10 June 2017 Guimarães.
- Holdsworth, J. and Apeh, E., 2017. An effective immersive cyber security awareness learning platform for businesses in the hospitality sector. 111-117.
- Apeh, E., 2017. Realtime Assessment and Feedback through Cyber Security Hackathons. In: CELebrate 2017 Regional Teaching and Learning Conference 13 June 2017 Bournemouth.
- Rogers, R., Apeh, E. and Richardson, C.J., 2017. Resilience of the Internet of Things (IoT) from an Information Assurance (IA) perspective. 110-115.
- Mohammed, S. and Apeh, E., 2017. A model for social engineering awareness program for schools. 392-397.
- Ambore, S., Apeh, E., Dogan, H., Richardson, C. and Osselton, D., 2017. Development of Human Factors and Cybersecurity Objectives for Mobile Financial Service (MFS). In: Ergonomics & Human Factors 2017 25-27 April 2017 Daventry, UK.
- Ward, J., Dogan, H., Apeh, E., Mylonas, A. and Katos, V., 2017. Using human factor approaches to an organisation’s bring your own device scheme. 396-413.
- Ambore, S., Richardson, C., Dogan, H., Osselton, D. and Apeh, E., 2016. Cyber Security for the Unbanked. In: International Conference of Big Data in Cyber Security 10 May 2016 Craiglockhart, Edinburgh.
- Rogers, R., Apeh, E. and Richardson, C., 2016. Detecting the Infringement of Personally Identifiable Information of the Elderly. In: BCS Quality Specialist Group Annual International Software Quality Management SQM/INSPIRE Conference 21-22 March 2016 Bournemouth.
- Ambore, S., Richardson, C., Dogan, H., Apeh, E. and Osselton, D., 2016. A “soft” approach to analysing mobile financial services socio-technical systems.
- Lin, C., Liu, D., Pang, W. and Apeh, E., 2015. Automatically predicting quiz difficulty level using similarity measures.
- Apeh, E., Žliobaite, I., Pechenizkiy, M. and Gabrys, B., 2012. Predicting multi-class customer profiles based on transactions: A case study in food sales. 213-218.
- Apeh, E.T., Gabrys, B. and Schierz, A., 2011. Customer profile classification using transactional data. 37-43.
- Apeh, E. and Gabrys, B., 2011. Change mining of customer profiles based on transactional data. 560-567.
- Apeh, E., 2006. Knowledge Transfer: From Research to Innovation. In: TheUK South West Regional Seminar on Competitive Advantage through Knowledge Transfer 1 November 2006 University of Plymouth. 3-7.
- Apeh, E.T., 2006. Clustering for data matching. 1216-1225.
- Reiter, E., Logan, A., Alvarez, L., Apeh, E., Libman, B. and Bradshaw, W.. Text generation from correlated alerts. Patent number US 20160217133 A1.
- Apeh, E., Gabrys, B. and Schierz, A., 2010. Robust Adaptive Algorithms for Relational Data Mining. In: The Proceedings of the 3rd School of Design, Engineering and Computing Poster Conference, Bournemouth University, UK.
- Apeh, E., Gabrys, B., Jones, M., Dexter, R. and Cooper, M., 2006. Application of Computational Intelligent to the Problem of Data Matching. In: The 4th International Summer School on Pattern Recognition (ISSPR).
- ACM, Member,
- BCS, Member,
- HEA, Fellow,
- IEEE, Member,
- IISP, Member,
- ISACA, Member,