Gurucul Risk Analytics (GRA)
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Gurucul Risk Analytics (GRA)
|Company (that provides the nominated product / solution / service)||Gurucul|
|Company size (employees)||190|
|Type of solution||Software|
In 3 bullets, summarize why this product or service is different from the competition and deserves recognition:
Gurucul GRA is a proven big-data security analytics solution that has been successfully deployed by government agencies and global Fortune 500 companies across the financial, healthcare, technology, retail and manufacturing sectors to detect and deter insider threats, account compromise and advanced external attacks. Customers include one of the world’s largest Internet payment companies, a top 5 US health insurer, large financial services firms, and government agencies.
Gurucul was the only vendor cited for meeting all five use cases outlined in the Market Guide for UEBA report by analyst firm Gartner: security management, insider threats, data exfiltration/DLP, identity access management, SaaS security, plus the extra qualifications for compliance and cyber fraud.
Gurucul has received industry recognition for its innovations in security analytics, including 2016 SC Awards in the US and Europe for Best Behavior Analytics/Enterprise Threat Detection, being named SINET 16 Innovator in both 2014 and 2015, Gartner Cool Vendor 2014, winning the 2016 CDM award for Best Insider Threat Prevention Solution, and more. Product review of Gurucul GRA by SC Magazine: “This is, hands-down, the most sophisticated example of behavioral analytics we have seen to date. While they are not the only player in this space, their product is well thought-out and it really works well.” http://www.scmagazine.com/gurucul-risk-analytics/review/4399/
Gurucul Risk Analytics (GRA) goes beyond rules, signatures and patterns with machine learning models based on big data from on-premises and cloud learning to detect abnormal user and entity behavior analytics (UEBA). GRA also includes the ability to reduce the surface area of access with identity analytics (IdA) with a risk-based approach for certifications, access requests and approvals, plus removing excess access, access outliers and cleaning-up orphan and dormant accounts. This holistic approach of UEBA and IdA together focuses on the compromise and misuse of identity, the root of modern threats.
GRA is built upon Hadoop and enables an open choice of big data to store data for value while leveraging 189 ready to use machine learning models for on-premises, cloud or hybrid environments.Over 30 data connectors speed ingestion of popular data sources, plus a flex connector enables any data source to ingest into GRA, no waiting on roadmaps or professional services. GRA focuses on 33 primary use cases for threats, access and cloud. More advanced customers can customize risk weightings plus develop their own machine learning models without coding within GRA.
For benefits, customers of GRA have seen the following results:
A financial firm reduced accounts and entitlements by 83% leveraging identity analytics (IdA). Adopting a risk-based approach the customer migrated to risk-based access certifications for requests and approvals and also deployed intelligent roles provided by GRA.
An insurance firm deployed Self Audits from GRA to over 60,000 end users to raise security awareness, provide deterrence and collaborate with users to detect identity theft and abuse. One privileged user detected an access anomaly when out of work on a weekday, the investigation later surfaced the account had been compromised for 3.5 years.