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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Al Mallah, R., López, D., Badu-Marfo, G., & Farooq, B. (2023). Untargeted poisoning attack detection in federated learning via behavior attestationAI. IEEE Access, 11, 125064-125079. External link
Al Mallah, R., Badu-Marfo, G., & Farooq, B. (2021, July). Cybersecurity threats in connected and automated vehicles based federated learning systems [Paper]. IEEE Intelligent Vehicles Symposium Workshops (IV Workshops 2021), Nagoya, Japan. External link
Al Mallah, R., Badu-Marfo, G., & Farooq, B. (2021). On the initial behavior monitoring issues in federated learning. IEEE Access, 9, 161046-161054. External link
Badu-Marfo, G., Al Mallah, R., & Farooq, B. (2024, June). Defense via behavior attestation against attacks in connected and automated vehicles based federated learning systems [Paper]. 99th IEEE Vehicular Technology Conference (VTC 2024-Spring), Singapore, Singapore (7 pages). External link
Badu-Marfo, G., Farooq, B., Mensah, D. O., & Al Mallah, R. (2023). An ensemble federated learning framework for privacy-by-design mobility behaviour inference in smart cities. Sustainable Cities and Society, 97, 104703 (17 pages). External link
