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Operationalizing Voice Security with Splunk: From AI Detection to Real-Time Action

Cisco IT describes how they operationalized their AI/ML-driven voice security system by integrating it with Splunk Cloud Platform. The architecture ingests millions of Call Detail Records (CDRs) from CUCM, Session Border Controllers, and cloud calling platforms, normalizes and enriches them with threat intelligence, then correlates them with AI risk scores. Operational dashboards provide executive overviews, behavioral trend analysis, geographic threat mapping, and risk-stratified investigation views. Automated alerting triggers incident tickets and blocking workflows when high-risk calls are detected, while cross-domain correlation links voice fraud to identity and network events. The integration delivered a 70% reduction in potential fraud losses, 60% reduction in manual investigation effort, and cut detection-to-mitigation time from hours to minutes.

    #security#machine-learning#logging#fraud-detection
Aug 04•6m read time•From blogs.cisco.com
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Table of contents
AI detection alone isn’t enoughThe data foundation: Building a scalable voice security pipelineTransforming detection into visibility: Operational dashboardsEnabling real-time security operationsBridging the gap between AI and operationsOperational impact: Real outcomes from integrationVoice security modernization as part of enterprise resilience
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