New Securonix Offering Enables Rapid Adoption of User Behavior Analytics to Detect and Respond to Cyber Threats, Insider Threats, Cloud Threats, and Fraud
ADDISON, Texas, July 27, 2017 (GLOBE NEWSWIRE) — Recognizing the high TCO and long time to value that security operations (SOC) analysts face when operationalizing an on premise security monitoring solution, Securonix today announced industry’s first SaaS-based UEBA solution. This new offering provides the benefits of Securonix UEBA 6.0 without the implementation or operational overhead of other security analytics tools.
“A SaaS based user behavior analytics solution is much needed to help security teams as they face the challenge of advanced cyber threats today,” said David Monahan, Research Director at analyst firm Enterprise Management Associates. “Organizations running security operations centers (SOCs) are not getting the level of context they need from their SIEM solutions alone, but purchasing an advanced analytics solution can be difficult to justify. A SaaS based UEBA solution nicely fits the bill.”
Securonix Cloud leverages the same machine learning, and threat model sharing/exchange capability available to customers of the enterprise version. “Detecting emerging threats demands robust detection techniques, with Securonix Cloud, organizations get the benefit of our automated threat model exchange service to rapidly detect and respond to new threats,” said Nitin Agale, SVP Products at Securonix. “Our threat models are continuously updated through learnings across our customers, partners and Securonix cyber threat labs. We are incorporating these learnings in real-time into Securonix Cloud to provide customers the benefit of our latest threat detection capabilities.”
With features now available through Securonix Cloud, security analysts can pinpoint advanced user based insider and cyber threats and prioritize the most critical incidents all from within an easy to use platform. Securonix Cloud benefits include:
- Rapid Time-to-Value – Instant deployment, easy to scale, no operational overhead
- Advanced Behavior Analytics – Leverages purpose built patented machine learning algorithms running on Spark engine to provide real time alerts on advanced threats
- Out-of-Box Packaged Apps – Packaged content for insider threat, cyber threat, cloud security and fraud analytics. Available vertical specific applications for patient data analytics and trade surveillance
- Automated Threat Model Update – Instant delivery new threat models that are continuously updated through learnings from customer deployments, partner collaboration, and Securonix cyber lab research
- Secure Architecture – Highly secure with encryption in transit and optionally at rest, dedicated tenants per customer, full RBAC and auditing capabilities
- Cloud to Cloud Integration – provides rich cloud connector framework to integrate directly with your cloud infrastructure, application and services
- Security Data Lake (SDL) Platform – is built on a big data platform that is massively scalable and cost effective. The Securonix SDL platform provides long term storage, analysis and retention capabilities at a predictable low cost
“Having powerful cyber security solutions is crucial to the protection of enterprise assets when facing sophisticated modern threats,” said Tanuj Gulati, Founder, and CTO of Securonix. “However, the agility to purchase, deploy and adapt your security solutions is equally important in today’s highly dynamic IT and cyber threat environment. Securonix Cloud delivers the industry’s top rated security analytics solution in an easily accessible SaaS model.”
Securonix Cloud provides an overall lower and predictable cost of ownership by introducing the industry’s first identity-based pricing for SaaS UEBA solutions. CISOs and security buyers are now able to accurately predict the cost of their security analytics effort instead of relying on highly variable pricing metrics such as EPS or data volumes. Securonix simplified pricing also relieves CISOs from the inherent security analysis limitations of data volume based pricing which restricted the amount of data they could use due to budgets – and hence reduced their accuracy of cyber threat detection.