Securonix is redefining the next generation of cyber-threat detection using the power of machine learning and big data. Our purpose-built security analytics solution uses machine learning to track and create baselines of user, account, and system behavior and detects the most advanced insider threats, cyber threats, and fraud activities in real time. Securonix extends threat detection with threat-hunting and automated incident response. SOC analysts can hunt across data sources, and respond with pre-built, automated playbooks. Globally, customers use Securonix to address their insider threat, cyber threat, cloud security, fraud, and application security monitoring requirements.
Securonix security analytics delivers real-time threat analysis and detection, log search, threat hunting and attack investigation via Spotter™, and comprehensive case/workflow management for end-to-end security management. The solution also provides out-of-the-box integrations with existing security products. Securonix Data Lake, Next-Gen SIEM and UEBA products are offered as on-premise enterprise software or delivered via the cloud.
Securonix is architected on a Hadoop big data infrastructure stack that optimizes data ingestion, context enrichment, real-time processing, and storage across separate components enabling efficient mass-scaling for large enterprises. This architecture is coupled with a new UI that realizes massive improvements in large deployments, and allows you to ingest and analyze large amounts of machine data in real-time. Securonix’s Hadoop stack allows for a Google-like search at massive scale. With Hadoop clustering, SOC analysts can perform data analysis at internet-scale instantaneously, and also leverage log-searching for over 600 different commercial security, network, and application products.