In a previous blog, we spoke about the importance of security enrichments in your network metadata. These serve as the foundation for threat hunters and analysts to test and query against hypotheses during an investigative process.
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Hsin Chen

Hsin Chen
Data Scientist
Hsin Chen is a data scientist at Vectra, where she researches security threats, runs analysis on big data, and trains machine learning models to detect cyberattacks. She implements various machine learning techniques, such as neural networks and unsupervised learning for anomaly detection. Hsin earned her master’s degree in mechanical engineering from Stanford University.
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Hsin Chen

Improving Threat-hunting Efficiency with the Multi-homed Attribute