Outputs (522)

MADONNA: browser-based malicious domain detection through optimized neural network with feature analysis. (2024)
Conference Proceeding
SENANAYAKE, J., RAJAPAKSHA, S., YANAI, N., KOMIYA, C. and KALUTARAGE, H. 2024. MADONNA: browser-based malicious domain detection through optimized neural network with feature analysis. In Meyer, N. and Grocholewska-Czuryło, A. (eds.) Revised selected papers from the proceedings of the 38th International conference on ICT systems security and privacy protection (IFIP SEC 2023), 14-16 June 2023, Poznan, Poland. IFIP advances in information and communication technology, 679. Cham: Springer [online], pages 279-292. Available from: https://doi.org/10.1007/978-3-031-56326-3_20

The detection of malicious domains often relies on machine learning (ML), and proposals for browser-based detection of malicious domains with high throughput have been put forward in recent years. However, existing methods suffer from limited accurac... Read More about MADONNA: browser-based malicious domain detection through optimized neural network with feature analysis..

Enhancing security assurance in software development: AI-based vulnerable code detection with static analysis. (2024)
Conference Proceeding
RAJAPAKSHA, S., SENANAYAKE, J., KALUTARAGE, H. and AL-KADRI, M.O. 2024. Enhancing security assurance in software development: AI-based vulnerable code detection with static analysis. In Katsikas, S. et al. (eds.) Computer security: revised selected papers from the proceedings of the International workshops of the 28th European symposium on research in computer security (ESORICS 2023 International Workshops), 25-29 September 2023, The Hague, Netherlands. Lecture notes in computer science, 14399. Cham: Springer [online], part II, pages 341-356. Available from: https://doi.org/10.1007/978-3-031-54129-2_20

The presence of vulnerable source code in software applications is causing significant reliability and security issues, which can be mitigated by integrating and assuring software security principles during the early stages of the development lifecyc... Read More about Enhancing security assurance in software development: AI-based vulnerable code detection with static analysis..

FedREVAN: real-time detection of vulnerable android source code through federated neural network with XAI. (2024)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., PETROVSKI, A., AL-KADRI, M.O. and PIRAS, L. 2024. FedREVAN: real-time detection of vulnerable android source code through federated neural network with XAI. In Katsikas, S. et al. (eds.) Computer security: revised selected papers from the proceedings of the International workshops of the 28th European symposium on research in computer security (ESORICS 2023 International Workshops), 25-29 September 2023, The Hague, Netherlands. Lecture notes in computer science, 14399. Cham: Springer [online], part II, pages 426-441. Available from: https://doi.org/10.1007/978-3-031-54129-2_25

Adhering to security best practices during the development of Android applications is of paramount importance due to the high prevalence of apps released without proper security measures. While automated tools can be employed to address vulnerabiliti... Read More about FedREVAN: real-time detection of vulnerable android source code through federated neural network with XAI..

Factors influencing mobile app user experience: an analysis of education app user reviews. (2024)
Conference Proceeding
ARAMBEPOLA, N., MUNASINGHE, L. and WARNAJITH, N. 2024. Factors influencing mobile app user experience: an analysis of education app user reviews. In 4th International conference on advanced research in computing 2024 (ICARC 2024), 21-24 February 2024, Belihuloya, Sri Lanka. Piscataway: IEEE [online], pages 223-228. Available from: https://doi.org/10.1109/ICARC61713.2024.10499727

In the competitive digital world, user reviews considered as the most vital source of user feedback, provide valuable insights that reflect the success of software applications in terms of user experience (UX). As user-generated content grows exponen... Read More about Factors influencing mobile app user experience: an analysis of education app user reviews..

Steps towards a philosophy of computing education. [Discussion paper]. (2024)
Conference Proceeding
MCDERMOTT, R., DANIELS, M. and FREZZA, S.T. 2024. Steps towards a philosophy of computer education. [Discussion paper]. In Mühling, A. and Jormanainen, I. (eds.) Proceedings of the 23rd Koli calling international conference on computing education research 2023, 13-18 November 2024, Koli, Finland. New York: ACM [online], article 20. Available from: https://doi.org/10.1145/3631802.3631817

Is it meaningful to talk about the philosophy of computing education? What is its subject matter and methods? Is it different from, or a subfield of, the philosophy of science education or the philosophy of technology education or the philosophy of e... Read More about Steps towards a philosophy of computing education. [Discussion paper]..

Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. (2023)
Conference Proceeding
JOHNSTON, P., ZARB, M. and MORENO-GARCIA, C.F. 2023. Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023),18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article number 10343048. Available from: https://doi.org/10.1109/fie58773.2023.10343048

This paper presents an experience report of online attendance and associated behavioural patterns during a module in the first complete semester undertaken fully online in the autumn of 2020, and the corresponding module deliveries in 2021 and 2022.... Read More about Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19..

A weighted ensemble of regression methods for gross error identification problem. (2023)
Conference Proceeding
DOBOS, D., DANG, T., NGUYEN, T.T., MCCALL, J., WILSON, A., CORBETT, H. and STOCKTON, P. 2023. A weighted ensemble of regression methods for gross error identification problem. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Symposium series on computational intelligence (SSCI 2023), 5-8 December 2023, Mexico City, Mexico. Piscataway: IEEE [online], pages 413-420. Available from: https://doi.org/10.1109/SSCI52147.2023.10371882

In this study, we proposed a new ensemble method to predict the magnitude of gross errors (GEs) on measurement data obtained from the hydrocarbon and stream processing industries. Our proposed model consists of an ensemble of regressors (EoR) obtaine... Read More about A weighted ensemble of regression methods for gross error identification problem..

MicroConceptBERT: concept-relation based document information extraction framework. (2023)
Conference Proceeding
SILVA, K., SILVA, T. and NANAYAKKARA, G. 2023. MicroConceptBERT: concept-relation based document information extraction framework. In Proceedings of the 7th SLAAI (Sri Lanka Association for Artificial Intelligence) International conference on artificial intelligence 2023 (SLAAI-ICAI 2023), 23-24 November 2023, Kelaniya, Sri Lanka. Piscataway: IEEE [online], article number 10365022. Available from: https://doi.org/10.1109...ICAI59257.2023.10365022

Extracting information from documents is a crucial task in natural language processing research. Existing information extraction methodologies often focus on specific domains, such as medicine, education or finance, and are limited by language constr... Read More about MicroConceptBERT: concept-relation based document information extraction framework..

Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. (2023)
Conference Proceeding
LINTILÄ, T. 2023. Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 15th International conference on education and new learning technologies (EDULEARN 2023), 3-5 July 2023, Palma, Spain. Valencia: IATED [online], pages 2121-2129. Available from: https://doi.org/10.21125/edulearn.2023.0638

This article describes research in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computer science students in Finland and Great Britain. The study has been conducted as action research, and it... Read More about Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK..

In search of a philosophy of computing education. (2023)
Conference Proceeding
MCDERMOTT, R., DANIELS,M. and FREZZA, S. 2023. In search of a philosophy of computing eduction. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343513. Available from: https://doi.org/10.1109/FIE58773.2023.10343513

In this paper, we present a preliminary description of the field of inquiry encompassed by the philosophy of computing education. We first attempt to identify a general framework for investigating characteristic questions of a philosophical nature th... Read More about In search of a philosophy of computing education..