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How Cisco IT Modernized Voice Security with AI

Cisco IT shares how it modernized enterprise voice security by replacing manual blocklists and static rules with an AI-driven composite risk-scoring engine. The system unifies telemetry from Cisco Unified Communications and Webex Calling into Splunk Cloud Platform, then applies Random Forest and XGBoost models enriched with FTC complaint data to detect toll fraud, robocalls, and spam in real time. The result: a ~70% reduction in potential toll fraud losses and a ~60% reduction in manual investigation effort. The post also notes that partner solutions (Mutare, SecureLogix, Pindrop) exist for organizations that prefer turnkey options, and frames the internal build as a reusable blueprint for enterprises looking to shift from reactive to predictive voice security.

    #machine-learning#logging#aiops
Aug 04•6m read time•From blogs.cisco.com
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The Challenge: When t raditional d efenses f all s hortA new approach: Applying observability to voiceThe solution: Building a composite risk-scoring engineThe results: Efficiency and securityA note on our approach: Flexibility in voice securityA c ollaborative e ffort: The r ole of Cisco c ustomer e xperienceA blueprint for modernizing voice security
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