Turning log data into real-time security intelligence

SQLstream’s operational intelligence platform transforms log and other machine data into real-time security intelligence. Where traditional SIEM and log monitoring tools fail, SQLstream manages with ease the increase in data volume and velocity coupled with more sophisticated known and unknown threat detection scenarios. With SQLstream, you will be able to:

• Identify complex time-sensitive and multi-location patterns by joining and correlating data streams from any number different types and sources.
• Add geospatial and movement analysis for identifying location-based patterns.
• Benefit from proven Big Data scalability for continuous analysis over high volume, high velocity, structured and unstructured data.
• Benefit from ease of development: SQLstream is easy to extend for different scenarios and more complex analytics, offering instant productivity with no hidden future obstacles.

Enterprise Security & Incident Detection

SQLstream’s streaming operational intelligence platform provides a real-time window into potential security threats and behavior patterns. Log and other machine data can be analyzed in real-time across all sources of data – network, firewalls, access points and applications. Incident details and alerts are raised immediately and streamed to dashboards and incident management systems for manual or automated handling and resolution.

Advanced Persistent Threats

Advanced Persistent Threats (APTs) seek to breach even the most sophisticated security defenses using a wide range of intrusion techniques over a period of time. APTs are difficult to detect as they are designed to remain hidden. SQLstream detects APTs through continuous monitoring of a vast amount of data from all systems over a prolonged period, looking for both time-based and spatial patterns of abnormal behavior hidden in the ‘business as usual’ data streams.

Benefits

• Detect and predict security threats in real-time by searching for known patterns and variations from normal behavior over time.
• Concurrent analysis for other operational applications such as performance monitoring, infrastructure alerts and consumer behavior using the data log data streams.
• Optimize accuracy by combine log data with external data sources such as social media, geo-position data and existing trend data from your data warehouse.

Resources