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Dr SHAILY KABIR's Outputs (3)

A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic (2023)
Journal Article
Hasan, M. M., Jahan, M., & Kabir, S. (2023). A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14037-14050. https://doi.org/10.1109/tits.2023.3305342

Trust establishment among vehicles is essential for vehicular ad hoc networks (VANETs) as it directly impacts the security and privacy of vehicular communication. Many trust estimation approaches have been introduced, however, they often suffer from... Read More about A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic.

An end-to-end authentication mechanism for Wireless Body Area Networks (2023)
Journal Article
Jahan, M., Tuz Zohra, F., Kamal Parvez, M., Kabir, U., Mohaimen Al Radi, A., & Kabir, S. (2023). An end-to-end authentication mechanism for Wireless Body Area Networks. Smart Health, 29, Article 100413. https://doi.org/10.1016/j.smhl.2023.100413

Wireless Body Area Network (WBAN) ensures a high-quality healthcare service to patients by providing remote and relentless monitoring of their health conditions. Nevertheless, the patients' health-related data are very sensitive and require security... Read More about An end-to-end authentication mechanism for Wireless Body Area Networks.

Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression (2023)
Journal Article
Kabir, S., Wagner, C., & Ellerby, Z. (2023). Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression. IEEE Transactions on Artificial Intelligence, 5(1), 3-22. https://doi.org/10.1109/TAI.2023.3234930

Most of statistics and AI draw insights through modelling discord or variance between sources (i.e., inter-source) of information. Increasingly however, research is focusing on uncertainty arising at the level of individual measurements (i.e., within... Read More about Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression.