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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
Abusitta, A., Halabi, T., Bataineh, A. S., & Zulkernine, M. (2024, June). Generative Adversarial Networks for Robust Anomaly Detection in Noisy IoT Environments [Paper]. IEEE International Conference on Communications (ICC 2024), Denver, CO, USA. 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. (2023). A visual cryptography based digital image copyright protection. Journal of Information Security and Applications, 3(2), 96-104. 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., Diwan, A., Hill, J., & Fung, B. (2021). AI-powered assembly code analytics for discerning malware intent. (Study Report - Graduate Studies n° W7714-217794). Unavailable
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
Abusitta, A., Halabi, T., & Abdul Wahab, O. (2021, August). ROBUST: Deep learning for malware detection under changing environments [Paper]. 1st Workshop on Adverse Impacts and Collateral Effects of Artificial Intelligence Technologies (AIofAI 2021), Montréal, Qc, Canada (13 pages). External link
Abusitta, A., Abdul Wahab, O., & Halabi, T. (2020). Deep learning for proactive cooperative malware detection system. (Report n° G-2020-23 EIW12). External link
Abusitta, A., Bellaïche, M., & Dagenais, M. (2019). Multi-cloud cooperative intrusion detection system: trust and fairness assurance. Annals of Telecommunications, 74(9-10), 637-653. External link
Abusitta, A., Bellaïche, M., Dagenais, M., & Halabi, T. (2019). A deep learning approach for proactive multi-cloud cooperative intrusion detection system. Future Generation Computer Systems-the International Journal of Escience, 98, 308-318. External link
Abusitta, A., Li, M., & Fung, B. (2019). AI-powered assembly code analytics for discerning malware intent. (Study Report - Graduate Studies n° W7714-207117). Unavailable
Abusitta, A., Aïmeur, E., & Abdul Wahab, O. (2020, August). Generative adversarial networks for mitigating biases in machine learning systems [Paper]. 24th European Conference on Artificial Intelligence (ECAI 2019), Santiago de Compostela, Spain (11 pages). External link
Abusitta, A. (2018). Theoretical and Applied Foundations for Intrusion Detection in Single and Federated Clouds [Ph.D. thesis, École Polytechnique de Montréal]. Available
Abusitta, A., Bellaïche, M., & Dagenais, M. (2018). On trustworthy federated clouds : a coalitional game approach. Computer Networks, 145, 52-63. External link
Abusitta, A., Bellaïche, M., & Dagenais, M. (2018, February). A trust-based game theoretical model for cooperative intrusion detection in multi-cloud environments [Paper]. 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN 2018), Paris, France (8 pages). Available
Abusitta, A., Bellaïche, M., & Dagenais, M. (2018). An SVM-based framework for detecting DoS attacks in virtualized clouds under changing environment. Journal of Cloud Computing : Advances, Systems and Applications, 7(9), 9 (18 pages). Available
Bellaïche, M., Abusitta, A., & Halabi, T. (2018, June). A cooperative game for online cloud federation formation based on security risk assessment [Paper]. 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud 2018) / 2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom 2018), Shanghai, China. External link
Esmaeilpour, M., Chaalia, N., Abusitta, A., Devailly, F.-X., Maazoun, W., & Cardinal, P. (2022). Bi-discriminator GAN for tabular data synthesis. Pattern Recognition Letters, 159, 204-210. External link
Girard, E., Yusri, R., Abusitta, A., & Aïmeur, E. (2023). An automated stable personalized selection for collaborative privacy education. International Journal on Integrating Technology in Education, 10(2), 16 pages. 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., & Abusitta, A. (2019, February). Toward secure resource allocation in mobile cloud computing : a matching game [Paper]. International Conference on Computing, Networking and Communications (ICNC 2019), Honolulu, HI, USA. External link
Halabi, T., Bellaïche, M., & Abusitta, A. (2018, August). Online allocation of cloud resources based on security satisfaction [Paper]. 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering (Trustcom/BigDataSE 2018), New York, N.Y.. External link
Halabi, T., Bellaïche, M., & Abusitta, A. (2018, June). Cloud security up for auction : a DSIC online mechanism for secure IaaS resource allocation [Paper]. Conference on Communications and Network Security (CSNET 2018), Paris, France (6 pages). External link
Khorramfar, M., Mtawa, Y. A., Abusitta, A., & Halabi, T. (2024, June). Credit-Based Client Selection for Resilient Model Aggregation in Federated Learning [Paper]. 59th Annual IEEE International Conference on Communications (ICC 2024), Denver, CO, USA. 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
Li, M., Diwan, A., Abusitta, A., & Fung, B. (2021). AI-powered assembly code analytics for discerning malware intent. (Study Report - Graduate Studies n° W7714-217794). Unavailable
Li, M., Diwan, A., Abusitta, A., Mahdavifar, S., & Fung, B. (2021). AI-powered assembly code analytics for discerning malware intent. (Study Report - Graduate Studies n° W7714-217794). Unavailable
Li, M., Abusitta, A., & Fung, B. (2020). AI-powered assembly code analytics for discerning malware intent. (Study Report - Graduate Studies n° W7714-207117). Unavailable
Sleit, A., AIMobaideen, W., Baarah, A. H., & Abusitta, A. (2023). An efficient pattern matching algorithm. Journal of Applied Sciences, 7(18), 2691-2695. External link
Sleit, A., & Abusitta, A. (2007). A visual cryptography bassed watermark technology for individual and group images. Journal of Systemics, Cybernetics and Informatics, 5(2), 24-32. External link
Sleit, A., & Abusitta, A. (2006, July). A watermark technology based on visual cryptography [Paper]. 10th World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando, Florida, USA. Unavailable
Sleit, A., & Abusitta, A. (2006, May). A watermark technology based on visual cryptography [Paper]. 4th International Multiconference on Computer Science and Information Technology (CSIT 2006), Amman, Jordan (11 pages). Unavailable
Yusri, R., Abusitta, A., & Aïmeur, E. (2021). Teens-Online: a Game Theory-Based Collaborative Platform for Privacy Education. International Journal of Artificial Intelligence in Education, 31(4), 726-768. External link
Yusri, R., Abusitta, A., & Aïmeur, E. (2020, July). A Stable Personalised Partner Selection for Collaborative Privacy Education [Paper]. 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2020), Genoa, Italy. External link
