Select Publications
Journal articles
2024, 'Cybersecurity Solutions and Techniques for Internet of Things Integration in Combat Systems', IEEE Transactions on Sustainable Computing, http://dx.doi.org/10.1109/TSUSC.2024.3443256
,2024, 'Harnessing Federated Learning for Digital Forensics in IoT: A Survey and Introduction to the IoT-LF Framework', IEEE Open Journal of the Communications Society, pp. 1 - 1, http://dx.doi.org/10.1109/ojcoms.2024.3492919
,2023, 'An explainable deep learning-enabled intrusion detection framework in IoT networks', Information Sciences, 639, http://dx.doi.org/10.1016/j.ins.2023.119000
,2023, 'The SAir-IIoT Cyber Testbed as a Service: A Novel Cybertwins Architecture in IIoT-Based Smart Airports', IEEE Transactions on Intelligent Transportation Systems, 24, pp. 2368 - 2381, http://dx.doi.org/10.1109/TITS.2021.3106378
,2023, 'Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions', IEEE Communications Surveys and Tutorials, 25, pp. 1775 - 1807, http://dx.doi.org/10.1109/COMST.2023.3280465
,2022, 'A new Intelligent Satellite Deep Learning Network Forensic framework for smart satellite networks', Computers and Electrical Engineering, 99, http://dx.doi.org/10.1016/j.compeleceng.2022.107745
,2020, 'A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports', IEEE Access, 8, pp. 209802 - 209834, http://dx.doi.org/10.1109/ACCESS.2020.3036728
,2020, 'A New Network Forensic Framework based on Deep Learning for Internet of Things Networks: A Particle Deep Framework', Future Generation Computers Systems
,2019, 'Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset', Future Generation Computer Systems
,2019, 'Forensics and Deep Learning Mechanisms for Botnets in Internet of Things: A Survey of Challenges and Solutions', IEEE Access, 7, pp. 61764 - 61785, http://dx.doi.org/10.1109/ACCESS.2019.2916717
,Conference Papers
2023, 'Digital Forensics based on Federated Learning in IoT Environment', in ACM International Conference Proceeding Series, pp. 92 - 101, http://dx.doi.org/10.1145/3579375.3579387
,2021, 'A Deep Learning-based Penetration Testing Framework for Vulnerability Identification in Internet of Things Environments', in Proceedings - 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2021, pp. 887 - 894, http://dx.doi.org/10.1109/TrustCom53373.2021.00125
,2020, 'Enhancing Network Forensics with Particle Swarm and Deep Learning: The Particle Deep Framework', Sydney, Australia, presented at 7th International Conference on Security and its Applications (CNSA 2020), Sydney, Australia, 28 March 2020 - 29 March 2020
,2017, 'Towards Developing Network forensic mechanism for Botnet Activities in the IoT based on Machine Learning Techniques', Springer International Publishing, Melbourne, Australia, presented at 9th International Conference, MONAMI 2017, Melbourne, Australia, 13 December 2017 - 15 December 2017, https://www.springerprofessional.de/en/towards-developing-network-forensic-mechanism-for-botnet-activit/15746852
,Preprints
2021, A Deep Learning-based Penetration Testing Framework for Vulnerability Identification in Internet of Things Environments, http://dx.doi.org/10.48550/arxiv.2109.09259
,2020, Enhancing network forensics with particle swarm and deep learning: The particle deep framework, http://dx.doi.org/10.48550/arxiv.2005.00722
,2018, Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset, http://dx.doi.org/10.48550/arxiv.1811.00701
,2017, Towards Developing Network forensic mechanism for Botnet Activities in the IoT based on Machine Learning Techniques, http://dx.doi.org/10.48550/arxiv.1711.02825
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