In a recent TechTarget article, Dan Sullivan declared Fortscale as one of the leading eight big data security analytics tool vendors. Sullivan defined five essential factors for gaining full benefits from the platform:
Unified data management
Support for multiple data types, including log, vulnerability and flow
Scalable data ingestion
Information security-specific analytic tools
Compliance reporting
Because unified data management is the bedrock of any big data security analytics product, Sullivan says as the data management platform stores and queries data across the enterprise, it also needs to balance data management features with cost and scalability.
“As Hadoop is a widely used big data management platform and associated ecosystem, it isn’t surprising to see it used as the basis for a number of big data security analytics platforms. Fortscale, for example, uses the Cloudera Hadoop distribution. This allows the Fortscale platform to scale linearly as new nodes are added to the cluster.”
Within the enterprise, it is important that big data security analytic tools are scalable. Sullivan further elaborates that “Fortscale employs machine learning and statistical analysis–collectively known as data science techniques–to adapt to changes in the security environment”. Using these techniques, the author states that Fortscale can “drive analysis based on data rather than just predefined rules”. When network baseline behaviors shift, changes are detected via machine learning algorithms and need no human intervention. Sullivan says Fortscale:
“. . .uses machine learning algorithms to continually assess changes to baseline activity and detect anomalous events. As the system detects these, it can generate alerts and provide contextual information about events.”
Read the full article here.
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