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

In our prior blog, we shared the strategic journey of how Cisco IT modernized our voice security posture by shifting from reactive, manual processes to a proactive, AI-driven defense. In this blog, we’ll dive deeper into the technical architecture that made this transformation possible. 

AI detection alone isn’t enough 

As the team responsible for managing Cisco’s global voice environment, we are tasked with protecting millions of calls from the growing threat of toll fraud, robocalls, and spam.  

To combat this, we developed an AI/ML-driven nuisance call detection engine. This was a critical initiative for Cisco IT, as the rising volume of toll fraud and spam had become a significant risk and a major drain on employee productivity. This engine uses behavioral analytics and machine learning to flag suspicious call patterns in real time. 

While our AI-driven detection engine was a major step forward, we quickly realized that simply identifying these…