Oracle Security Monitoring and Analytics

Analytics-Driven Security Monitoring

Oracle Security Monitoring and Analytics (SMA) Cloud Service is an integrated SIEM and UEBA solution for rapid detection, investigation, and remediation of a broad range of security threats and attacks across your IT.

  • A simplified and unified dashboard that gives you a quick snapshot of your security posture.

  • A quick snapshot of risky users and risky assets. This is your top 10 list to ensure your critical users and assets are protected.

  • SMA shows quickly that a user was subjected to multiple attacks identified by various kill-chain steps such as recon, infiltration, lateral movement, etc.

  • Perform deep forensic investigation and initiate quick response with remediation or automated ticketing for further investigation.


Continuous and Adaptive Security

Continuous and Adaptive Security

  • Continuous detection of threats in real time
  • Adaptive response to security incidents
  • Risk analysis through identity and context awareness
  • Trust-based review system uses machine learning and adaptive security
  • Architecture supports seamless integration of people, process, and technology
White paper: Oracle Identity SOC with SMA (PDF)
Continuous Detection of Threats

Continuous Detection of Threats

  • Get visibility into security posture
  • Understand who did what, where, and when?
  • Monitor security configurations and activities in even unsanctioned IT systems
  • Monitor OS, apps, cloud infrastructure, and cloud apps
  • Enforce enterprise security configurations on both old and new IT
Adaptive Response to Security Incidents

Adaptive Response to Security Incidents

  • Ensure the right security controls are on your IT
  • Dynamic security configurations based on changing industry standards
  • Monitor for authentication and authorization of users, apps, and data
  • Evaluate risky users and assets based on their behavior
  • Assess both old and new IT for behavior
Machine Learning Based Review System

Machine Learning Based Review System

  • Continuous monitoring of users, apps, data, and configurations
  • Dynamic scoring of apps and users for adjusting the baseline behavior
  • Built-in use cases for anomaly detection
  • Analyze and score each user by app
  • Automated response based on risk score and correlation of security events
Analytics for Security Operations
Analytics for Security Operations
Anomaly detection and machine learning are helping us to find bad guys that have otherwise bypassed our rules-based prevention systems
—Eric Ahlm, Research Director, Gartner

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