Databricks
Case Studies
Barracuda Networks' Use of Machine Learning on Databricks Lakehouse for Phishing Attack Prevention
Overview
Barracuda Networks' Use of Machine Learning on Databricks Lakehouse for Phishing Attack PreventionDatabricks |
Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Application Development Platforms | |
Education Retail | |
Procurement | |
Predictive Maintenance Retail Store Automation | |
Data Science Services | |
Operational Impact
The integration of Databricks Lakehouse Platform into Barracuda Networks' operations has resulted in a more efficient and effective phishing attack detection and prevention system. The use of the Databricks Feature Store and Managed MLflow has simplified the process of feature engineering and model deployment, allowing the team to move faster and block more malicious emails. The system's improved efficiency has also resulted in a higher detection rate, leading to improved customer protection and satisfaction. The team is now able to publish a new table frequently in Delta, update the features every day, and use these to determine whether an incoming email is an attack or not. The team is looking forward to continuing to implement new Databricks features to enhance their customers' experience further. | |
Quantitative Benefit
Barracuda is now blocking tens of thousands of malicious emails daily from reaching millions of mailboxes across thousands of customers. | |
The team can now move much faster with the help of Databricks Lakehouse Platform. | |
The use of Databricks Feature Store and Managed MLflow has greatly reduced the time the team spends developing ML models. | |