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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Abusitta, A., Li, M. Q., & Fung, B. C. M. (2024). Survey on explainable AI : techniques, challenges and open issues. Expert Systems With Applications, 255, 124710 (18 pages). External link
Alhashemi, W. J., Fung, B. C. M., Abusitta, A., & Fachkha, C. (2024, November). CSGraph2Vec: Distributed Graph-Based Representation Learning for Assembly Functions [Paper]. IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE 2024), Taichung, Taiwan. External link
Abusitta, A., de Carvalho, G. H. S., Abdul Wahab, O., Halabi, T., Fung, B. C. M., & Al Mamoori, S. (2023). Deep learning-enabled anomaly detection for IoT systems. Internet of Things, 21, 100656 (13 pages). External link
Abusitta, A., Abdul Wahab, O., & Fung, B. C. M. (2021, July). VirtualGAN: Reducing mode collapse in generative adversarial networks using virtual mapping [Paper]. International Joint Conference on Neural Networks (IJCNN 2021), Shenzhen, China (6 pages). External link
Abusitta, A., Li, M. Q., & Fung, B. C. M. (2021). Malware classification and composition analysis: A survey of recent developments. Journal of Information Security and Applications, 59, 102828 (17 pages). External link
Guerrouj, L., Kermansaravi, Z., Arnaoudova, V., Fung, B. C. M., Khomh, F., Antoniol, G., & Guéhéneuc, Y.-G. (2017). Investigating the relation between lexical smells and change- and fault-proneness: an empirical study. Software Quality Journal, 25(3), 641-670. External link
Halabi, T., Abusitta, A., Carvalho, G. H. S., & Fung, B. C. M. (2022, July). Incentivized Security-Aware Computation Offloading for Large-Scale Internet of Things Applications [Paper]. 7th International Conference on Smart and Sustainable Technologies (SpliTech 2022), Bol, Croatia (6 pages). External link
Halabi, T., Bellaïche, M., & Fung, B. C. M. (2022, November). Towards Adaptive Cybersecurity for Green IoT [Paper]. IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS 2022), Bali, Indonesia. External link
Li, M. Q., Fung, B. C. M., & Abusitta, A. (2022, July). On the Effectiveness of Interpretable Feedforward Neural Network [Paper]. International Joint Conference on Neural Networks (IJCNN 2022), Padua, Italy (8 pages). External link
