Cite
A Framework for Anomaly Detection in Time-Driven and Event-Driven Processes Using Kernel Traces.
MLA
Ezeme, Okwudili M., et al. “A Framework for Anomaly Detection in Time-Driven and Event-Driven Processes Using Kernel Traces.” IEEE Transactions on Knowledge & Data Engineering, vol. 34, no. 1, Jan. 2022, pp. 1–14. EBSCOhost, https://doi.org/10.1109/TKDE.2020.2978469.
APA
Ezeme, O. M., Mahmoud, Q. H., & Azim, A. (2022). A Framework for Anomaly Detection in Time-Driven and Event-Driven Processes Using Kernel Traces. IEEE Transactions on Knowledge & Data Engineering, 34(1), 1–14. https://doi.org/10.1109/TKDE.2020.2978469
Chicago
Ezeme, Okwudili M., Qusay H. Mahmoud, and Akramul Azim. 2022. “A Framework for Anomaly Detection in Time-Driven and Event-Driven Processes Using Kernel Traces.” IEEE Transactions on Knowledge & Data Engineering 34 (1): 1–14. doi:10.1109/TKDE.2020.2978469.