Gurucul Supports Open Choice for UEBA Data Lakes

Business Wire

Enables Customers to Deploy its Advanced Security Analytics Engine on Leading Big Data Platforms

NATIONAL HARBOR, Md.--(BUSINESS WIRE)-- Gurucul, a leader in user and entity behavior analytics (UEBA) and identity analytics (IdA) for on-premises and the cloud, today announced at the Gartner Security & Risk Management Summit that the Gurucul Risk Analytics (GRA) platform can be deployed on any leading big data infrastructure to protect IT investments, eliminate data duplication and reduce storage fees. This open choice enables customers to layer Gurucul’s advanced security analytics engine on top of existing and new Hadoop, Cloudera, Hortonworks, MapR and Elastic/ELK deployments.

According to Gartner, Inc.: “The UEBA market is poised for major opportunities and transformations; it will grow at a CAGR of 48% between 2015 and 2020. Growth is fueled by buyer demand for insider threat and compromised account detection features missed by legacy security monitoring systems that lack advanced analytics.”¹

Organizations increasingly want to use their own data lake infrastructures to perform advanced security analytics, rather than create a second big data store on a UEBA, SIEM or other security vendor’s platform. By providing open choice, Gurucul computes and stores security intelligence on customer data lakes to avoid any duplication and increased storage/indexing fees. The ability to quickly and accurately ingest and analyze user activity data, including the contents of a customer’s data lake, for advanced security analytics has become a key differentiator for Gurucul GRA.

“Threat-conscious enterprises are demanding visibility into user and otherwise unknown malicious activities that is unavailable from legacy security monitoring systems and can only be achieved using advanced behavior analytics and UEBA,” said Nilesh Dherange, CTO of Gurucul. “SIEM and log management platforms lack the intelligence required to detect account compromise attacks by outsiders and insider threats.”

Real World Use Cases
One large health insurance organization is using Gurucul on top of hundreds of Hortonworks big data nodes. It is applying advanced analytics to over 15 million identities belonging to employees, partners and customers that risk score activity and identify conditions that require further investigation by security analysts or automated risk response such as adaptive access management, issuing self audits or remediating privileged access outliers. Meanwhile, a large financial institution has deployed Gurucul advanced security analytics with its custom cloud big data lake on AWS to risk score access and activity, reduce risks and detect unknown threats.

About Gurucul Risk Analytics
Gurucul Risk Analytics (GRA) is a multi-use UEBA platform with an open architecture that supports a choice of big data for scale, the ability to ingest virtually any dataset for desired attributes and includes configurable prepackaged analytics. In addition, Gurucul STUDIO enables customers to create custom machine learning models to meet unique requirements without coding and minimal data science knowledge. GRA ingests and analyzes huge volumes of data generated when users access and interact with business applications, in both the data center and the cloud, to generate risk scores, identify security threats and prevent data breaches. The Gurucul GRA platform has been successfully deployed by government agencies and Global Fortune 500 companies.

About Gurucul
Gurucul is changing the way enterprises protect themselves against insider threats, account compromise and data exfiltration on-premises and in the cloud. The company’s user and entity behavior analytics and identity access intelligence technology use machine learning anomaly detection and predictive risk-scoring algorithms to reduce the attack surface for accounts, unnecessary access rights and privileges, and to identify, predict and prevent breaches. Gurucul technology is used globally by organizations to detect insider threats, account compromise, IP and data theft, external attacks and more. The company is based in Los Angeles. To learn more, visit http://www.gurucul.com/ and follow us on LinkedIn and Twitter.

¹ Gartner, Inc., Forecast Snapshot: User and Entity Behavior Analytics, Worldwide, 2017, 3 March 2017, Avivah Litan