Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization. Abstract: As the attack surfaces of large enterprise networks grow, anomaly ...

We introduce a multidimensional anomaly detection method that is sensitive to anomalous activity over a diverse set of attributes. We show that higher order ...

Alexandrov, "Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization," 2020 IEEE International Conference on Intelligence and Security ...

The user's activity reveals time- and device-based predictable patterns that deviate from the single anomalous log-on. Extending tensor factorization methods in ...

Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization. As the attack surfaces of large enterprise networks grow, anomaly detection ...

pyCP_APR is a Python library for tensor decomposition and anomaly detection that is developed as part of the R&D 100 award wining SmartTensors project.

Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization, M. Eren, J. Moore, and B.S. Alexandrov. Proceedings of 18th IEEE ...

Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization, M. Eren, J. Moore, and B.S. Alexandrov. Proceedings of 18th IEEE ...

Mar 12, 2024 · Multi-Dimensional Anomalous Entity Detection via. Poisson Tensor Factorization. General-Purpose Unsupervised Cyber. Anomaly Detection via Non- ...

... Anomaly Detection via Non-Negative Tensor Factorization. Article. Full-text ... Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization.