# Cisco and Splunk Enhance Voice Security with AI-Driven Efficiency

> Cisco’s integration of AI and Splunk Cloud Platform marks a pivotal shift in voice security, turning reactive measures into proactive defenses against threats like toll fraud and spam. Discover how this innovative approach enhances security and productivity.

**Source**: blogs.cisco.com | **Published**: 2026-08-04 | **Type**: article

## Key Facts

- Cisco's AI/ML engine cut potential fraud losses by 70%, showcasing effective risk management.
- Integration with Splunk reduced threat response time from hours to minutes, enhancing operational efficiency.
- Real-time dashboards improved decision-making, aligning IT and SOC teams with enterprise security goals.
- Centralized data pipelines enabled analysis of millions of calls, driving scalability in voice security operations.
- Automated workflows decreased manual investigation effort by 60%, revealing vulnerabilities in traditional methods.

## Summary

Cisco has significantly transformed its voice security operations by integrating AI-driven detection with the Splunk Cloud Platform, marking a strategic shift from reactive to proactive security measures. This evolution is crucial as the company faces increasing threats from toll fraud, robocalls, and spam, which not only jeopardize security but also drain employee productivity. By operationalizing insights from AI, Cisco aims to mitigate these risks effectively and enhance its overall security posture.

The foundation of this transformation lies in the development of an AI and machine learning (ML)-driven nuisance call detection engine. This engine analyzes call patterns in real time, identifying suspicious activities that could indicate fraud. However, Cisco recognized that detection alone would not suffice. To address the complexities of voice security, the company needed a robust system capable of processing vast amounts of Call Detail Records (CDRs) and turning raw data into actionable intelligence. Splunk serves as the backbone of this system, facilitating the ingestion, normalization, and correlation of data from various sources, including Cisco’s Unified Communications Manager and Session Border Controllers.

The integration of Splunk allows Cisco to create a unified data layer that enhances visibility across its voice environment. This centralized approach provides a comprehensive operational view, enabling IT and security teams to respond swiftly to threats. Key operational dashboards have been developed to present critical information, such as the overall security posture, threat trends, and geographic risk assessments. These tools empower decision-makers at all levels of the organization to act on real-time data, improving the speed and effectiveness of threat management.

Moreover, the operational capabilities of Splunk extend beyond visualization. Automated alerts and incident response workflows enable Cisco to react to high-risk calls almost instantaneously. This integration not only streamlines operations but also enhances cross-domain security correlation, allowing teams to identify broader patterns of compromise that may indicate more significant security breaches. For instance, a spike in voice fraud activity may correlate with unusual login patterns, signaling potential credential theft.

The results of this integrated approach have been substantial. Cisco has reported a 70% reduction in potential total fraud losses and a significant decrease in the time required to detect and mitigate threats—from hours to mere minutes. Additionally, the automation of risk stratification has allowed analysts to focus on the most critical threats, resulting in a 60% reduction in manual investigation efforts. This operational efficiency not only strengthens Cisco's security posture but also contributes to overall business resilience.

As companies look to modernize their own security infrastructure, Cisco's experience highlights several key lessons. Detection mechanisms must be coupled with operational visibility to be effective. Centralized data pipelines are essential for scalable analysis, while intuitive visualization tools accelerate decision-making processes. Automation plays a critical role in reducing response times and alleviating the operational burden on security teams. Integrating these elements into existing workflows enhances an organization’s security posture and prepares it for future challenges.

Looking ahead, the trend toward integrating advanced analytics and automation in security operations will likely intensify. Companies that invest in similar technologies will not only improve their threat response capabilities but also position themselves to navigate the increasingly complex landscape of digital security. As the threat environment evolves, the ability to operationalize AI-driven insights will become a decisive factor in maintaining competitive advantage and ensuring enterprise resilience.

## Entities

- **Companies**: Cisco
- **Products**: Splunk Cloud Platform, Cisco Unified Communications Manager (CUCM), Session Border Controllers (SBCs)
- **Technologies**: AI, ML, behavioral analytics

## Key Concepts

voice security, AI-driven detection, real-time action, toll fraud, robocalls, automated workflows, data visualization, enterprise resilience

## Definitions

- **AI/ML**: Artificial Intelligence and Machine Learning technologies used to detect patterns and anomalies in data.
- **CDR**: Call Detail Record, a data record produced by a telephone exchange that documents the details of a call.
- **SBC**: Session Border Controller, a device used in VoIP networks to manage and secure voice traffic.
- **nuisance call detection**: A system designed to identify and mitigate unwanted calls such as spam and fraud.
- **risk stratification**: The process of categorizing risks based on their severity to prioritize response efforts.

## Use Cases

- Automated alerting for high-risk calls
- Real-time visualization of voice security posture
- Cross-domain security correlation
- Risk-based prioritization of threats
- Operational dashboards for decision-making
- Integration of AI/ML detection with operational workflows

## Frequently Asked Questions

**What is the main benefit of using Splunk for voice security?**

Splunk provides a centralized platform for ingesting and analyzing Call Detail Records, enabling real-time visibility and automated responses to threats. This integration enhances operational efficiency and reduces response times.

**How does AI/ML contribute to voice security?**

AI/ML technologies help in detecting behavioral anomalies and flagging suspicious call patterns, which is crucial for identifying potential fraud and spam. This proactive approach allows for quicker mitigation of threats.

**What are Call Detail Records (CDRs) and why are they important?**

CDRs are data records that contain detailed information about phone calls, such as duration and participants. They are essential for analyzing call patterns and identifying potential security threats.

**What role does automation play in voice security operations?**

Automation streamlines the incident response process by triggering alerts and initiating workflows without manual intervention. This reduces the operational burden on IT and SOC teams and speeds up threat response.

**Why is operational visibility critical in voice security?**

Operational visibility allows teams to monitor and analyze threats in real-time, ensuring that they can respond quickly and effectively. It transforms detection into actionable insights that enhance overall security posture.

## Links

- [Read on Welcome.AI](https://welcome.ai/content/cisco-and-splunk-enhance-voice-security-with-ai-driven-efficiency)
- [Original source](https://blogs.cisco.com/cisco-on-cisco/operationalizing-voice-security-with-splunk-from-ai-detection-to-real-time-action)
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Source: Welcome.AI | https://welcome.ai/content/cisco-and-splunk-enhance-voice-security-with-ai-driven-efficiency