Enterprise security has become a big data problem. The variety, velocity, and volume of data required to detect and contain sophisticated attacks require completely new approaches to harness and extract actionable insight from it. Because time is of the essence, traditional information retrieval methods that query databases or search repositories are not scalable, fast or precise enough to detect the subtle signals, relationships, patterns, contexts and anomalies that indicate the presence of a sophisticated attack or infection. And because Smaarts can efficiently look at all the data (volume), in real-time as the data streams (velocity), and is optimized for handling unstructured, semi-structured and structured data (variety), it analyzes all data concurrently without the need to aggregate incoming streams.

SmaartsTM, a software company headquartered in San Mateo, CA provides the SOC analyst advanced software that accelerates incident response by providing real-time and synchronized historical visibility into combinations and sequences of observable behaviors that map directly to the Cyber Kill Chain. Smaarts works with a broader set of data types than any other security analytics product. It consumes streaming data from multiple concurrent sources and parses each stream into its constituent data elements – from syslog feeds and anti-malware alerts, to Twitter feeds and historical data presented as a stream. It can also query Active Directory, proxy servers and external threat intelligence services in runtime. In the world of Big Data, the richer and more varied the data, the higher the accuracy of the results.

Smaarts is particularly adept at handling unstructured and semi-structured data – device alerts, syslog flows, JSON objects (including Tweets), email messages, documents and more.Only recently has attention been paid to optimize and automate the process of detecting and containing the attacks that get through. More than half of successful attacks extract corporate data within seconds or minutes of infection. Unfortunately, it typically takes days, sometimes weeks, just to detect compromises. This is a vexing problem for almost every organization.

Smaarts is a human-machine collaborative system that leverages both the observational powers of human intuition and institutional knowledge to automate the complex work flows that are manually performed by most SOC analysts today.