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About Marwa
Dr. Marwa Keshk serves as Lecturer in Cyber Security at the School of Professional Studies, University of New South Wales (UNSW) Canberra. She completed her PhD in Cyber Security and Privacy Preservation in 2021 and her Master’s degree in Evolutionary Computation in 2017, both at UNSW. Prior to that, she obtained her Bachelor’s degree in Computer Science from the Faculty of Computers and Information at Helwan University, Egypt, in 2012. As a PhD candidate, she conducted research at Data61-CSIRO, Australia's national science agency. Her research specializes in the intersection of cyber security and artificial intelligence, with emphasis on privacy preservation, anomaly detection, and threat intelligence. She employs computational intelligence, machine learning, statistical methods, and emerging technologies to address challenges in cyber-physical systems and IoT networks.
Keshk was awarded the UNSW Tuition Fee Scholarship for her PhD from 2018 to 2021 and the Data61/CSIRO Scholarship from 2019 to 2021. Her publication record includes significant contributions such as "IoTBoT-IDS: A novel statistical learning-enabled botnet detection framework for protecting networks of smart cities" (Sustainable Cities and Society, 2021), "A Privacy-Preserving-Framework-Based Blockchain and Deep Learning for Protecting Smart Power Networks" (IEEE Transactions on Industrial Informatics, 2020), "Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions" (IEEE Communications Surveys & Tutorials, 2023), "Swarm Optimization-Based Federated Learning for the Cyber Resilience of Internet of Things Systems Against Adversarial Attacks" (IEEE Transactions on Consumer Electronics, 2024), "An explainable deep learning-enabled intrusion detection framework in IoT networks" (Information Sciences, 2023), and "Privacy-Preserving Schemes for Safeguarding Heterogeneous Data Sources in Cyber-Physical Systems" (IEEE Access, 2021). With over 2,169 citations according to Google Scholar, her work has notably influenced advancements in cybersecurity for IoT and cyber-physical systems.
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