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- W4313731698 abstract "The railway cable infrastructure has become a major concern worldwide due to attacks and failures causing substantial economic losses and destruction. This research seeks to rapidly detect cable threats and send timely alerts by integrating cross-sectional explorative analytics with a three-stage detection approach in a sensor network used on the railway cable infrastructure protection. Existing approaches have delayed gaps that are addressed in this paper. Experimental results using real-life sensors and publicly available data demonstrate that the proposed detection approach is sufficiently reliable, accurate and robust for detecting suspicious behavior on railway cable infrastructure. The results of this paper can be used as a reference guide to understand railway cable infrastructure protection gaps and enrich the literature on IoT (internet-of-things) in securing railway cable infrastructure." @default.
- W4313731698 created "2023-01-08" @default.
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- W4313731698 date "2023-01-01" @default.
- W4313731698 modified "2023-09-23" @default.
- W4313731698 title "Towards Railway Cable Infrastructure Protection: Turning Cross-Sectional Explorative Analytics to Answers" @default.
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- W4313731698 doi "https://doi.org/10.1007/978-3-031-24848-1_19" @default.
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