Interset unlocks the power of user and entity behavioral analytics (UEBA) and machine learning to furnish security professionals with the most-advanced technique for executing rapid and accurate threat-detection analysis. The technology will accelerate Micro Focus' delivery of a more-robust UEBA offering and help drive deeper data insights across security and operations that are necessary to execute on the company's SecOps Analytics vision.
"Security is at the heart of every organization, and perhaps never more so than as they implement their digital transformation initiatives and leverage emerging technologies to better predict and take action on credible threats," said John Delk, Senior Vice President and General Manager of Security, Risk & Governance at Micro Focus. "Micro Focus recognized that an even more advanced analytics ecosystem was needed to assist in this journey, and we identified Interset as a critical addition to our strategy."
Interset has achieved a strong reputation in the market with software that has been proven in key verticals – energy, critical infrastructure, high-tech, aerospace, defense and government – where threat detection is at a premium. The technology will supplement Micro Focus' Big Data analytics software, Vertica, and add additional value to Micro Focus ArcSight – the world's leading real-time correlation engine – to deliver a highly differentiated cyber-security solution.
"The combination of the Interset technology with Micro Focus' broad security portfolio is a powerful combination that will produce a level of protection that will be unmatched in the market," said Mark Smialowicz, Interset's Chief Executive Officer. "Our 'Data In, Intelligence Out' methodology will deliver an even-more complete set of benefits for our combined customers – allowing them to leverage near real-time information to address both immediate- and long-term threats."
Key attributes of the Interset technology include:
Extensible analytics – With multiple use cases out of the box – including inside threats, targeted attacks, and fraud – the technology eliminates the need for expensive product consultations and customization.
Principled math – The software utilizes a growing library of more than 350 proven machine-learning and advanced-analytics models, applying them to both events and entities, to yield a highly accurate means of detecting, connecting, and quantifying high-risk behaviors.
Scalable Big Data – The flexible, open platform combines an advanced-analytics engine with open-source, big-data technology, including Kafka, Spark, Phoenix, Hadoop, HBase, Elasticsearch, ZooKeeper, d3, and Kibana. It can be deployed in the Vertica, Hortonworks or Cloudera infrastructures, scaling to meet the needs of the largest, most-sophisticated environments.