Use Case: Advanced Threat Detection
Data and network security threats, whether internal or external, need to be identified and addressed as the act occurs. MetaGrid’s advanced threat detection capabilities handle anomaly detection on any type of data without prior rules or signatures, closing the gap left by single-purpose security tools.
A global critical IT infrastructure company, processing nearly a hundred billion transactions per day was using a highly segmented and reactive approach to security and threat detection. Additionally, they were spending a lot of money and time centralizing the data for analysis, which compromised real-time insight. In an environment experiencing one million transactions per second, the company was using high-cost, Hadoop-based tools that didn’t scale to address big data needs. Moreover, existing solutions were not effective in handling rate anomaly detection for VPN logins and entry points.
- Neural Foam Anomaly Detection
After deployment, the company:
- Delivered real-time insight into unusual VPN login points and frequency
- Cut operational costs by using one solution to collect and analyze data from different systems and sources
- Found and automatically addressed threats/patterns before they became an issue
- Saved time and money while scaling visibility by distributing computation to the data and using MetaGrid’s streaming queries feature to correlate data from diverse sources