By Sara Salim

Journal articles

Salim S; Moustafa N; Hassanian M; Ormod D; Slay J, 2024, 'Deep-Federated-Learning-Based Threat Detection Model for Extreme Satellite Communications', IEEE Internet of Things Journal, 11, pp. 3853 - 3867, http://dx.doi.org/10.1109/JIOT.2023.3301626

Salim S; Turnbull B; Moustafa N, 2024, 'A Blockchain-Enabled Explainable Federated Learning for Securing Internet-of-Things-Based Social Media 3.0 Networks', IEEE Transactions on Computational Social Systems, 11, pp. 4681 - 4697, http://dx.doi.org/10.1109/TCSS.2021.3134463

Salim S; Moustafa N; Reisslein M, 2024, 'Cybersecurity of Satellite Communications Systems: A Comprehensive Survey of the Space, Ground, and Links Segments', IEEE Communications Surveys and Tutorials, http://dx.doi.org/10.1109/COMST.2024.3408277

Salim S; Moustafa N; Turnbull B; Razzak I, 2022, 'Perturbation-enabled Deep Federated Learning for Preserving Internet of Things-based Social Networks', ACM Transactions on Multimedia Computing, Communications and Applications, 18, http://dx.doi.org/10.1145/3537899

Salim S; Turnbull B; Moustafa N, 2022, 'Data analytics of social media 3.0: Privacy protection perspectives for integrating social media and Internet of Things (SM-IoT) systems', Ad Hoc Networks, 128, http://dx.doi.org/10.1016/j.adhoc.2022.102786

Conference Papers

Salim S; Ali I; Elsawah S, 2024, 'A Secure Simulation-optimisation Framework for Fleet Mix Problem: A Defence-based Real-world Application', in GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, pp. 207 - 210, http://dx.doi.org/10.1145/3638530.3654170

Moustafa N; Salim S; Turnbull B, 2020, 'Privacy-Encoding Models for Preserving Utility of Machine Learning Algorithms in Social Media', Guangzhou, China, presented at The 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Guangzhou, China, 31 December 2020

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