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Documents dont l'auteur est "Fung, Benjamin C. M."

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Nombre de documents: 8

Article de revue

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). Lien externe

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). Lien externe

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. Lien externe

Communication écrite

Alhashemi, W. J., Fung, B. C. M., Abusitta, A., & Fachkha, C. (novembre 2024). CSGraph2Vec: Distributed Graph-Based Representation Learning for Assembly Functions [Communication écrite]. IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE 2024), Taichung, Taiwan. Lien externe

Halabi, T., Abusitta, A., Carvalho, G. H. S., & Fung, B. C. M. (juillet 2022). Incentivized Security-Aware Computation Offloading for Large-Scale Internet of Things Applications [Communication écrite]. 7th International Conference on Smart and Sustainable Technologies (SpliTech 2022), Bol, Croatia (6 pages). Lien externe

Li, M. Q., Fung, B. C. M., & Abusitta, A. (juillet 2022). On the Effectiveness of Interpretable Feedforward Neural Network [Communication écrite]. International Joint Conference on Neural Networks (IJCNN 2022), Padua, Italy (8 pages). Lien externe

Halabi, T., Bellaïche, M., & Fung, B. C. M. (novembre 2022). Towards Adaptive Cybersecurity for Green IoT [Communication écrite]. IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS 2022), Bali, Indonesia. Lien externe

Abusitta, A., Abdul Wahab, O., & Fung, B. C. M. (juillet 2021). VirtualGAN: Reducing mode collapse in generative adversarial networks using virtual mapping [Communication écrite]. International Joint Conference on Neural Networks (IJCNN 2021), Shenzhen, China (6 pages). Lien externe

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