With the wide varieties and inherent complexities of SIP and VoIP protocols, real-time communication (RTC) networks can only stand to benefit from the added value of behavioral analytics and machine learning. Specific to the RTC environment, behavior analysis combined with anomaly detection will be crucial for detecting many types of fraudulent activity. Whether it be in the core of the service provider network or delivered as a service to the end customer, behavioral analytics has an important role to play in securing RTC environments.
Real-Time Communications Behavioral Analytics Features & Benefits
- Using analytics for the anomaly detection process of searching through RTC networks and infrastructure for coordinated / advanced threats that are evading existing security solutions and defenses such as your SBCs and FWs.
- Detect and stop toll fraud by continually analyzing metrics such as call attempts, call duration, calling number, called number, types of calls (Local, Long Distance, International) during working hours as well as non-working hours.
- Telephony denial of service (T-DoS) attacks can take on many forms. Some can be identified by basic volumetric violations. However, some are far more clever and disguise themselves. This is where behavioral analytics can be an integral component in the layered security detail.
- One of the many benefits of using behavioral analytics in your layered security approach, is that a well-defined baseline of what is categorized as “normal” activity is established. Deviations from this baseline can be quickly identified and mitigated
- As the FCC is encouraging service providers to take measures to address robocalling, implementing solutions have become a priority. With known bad actor databases and the capabilities of behavioral analytics, a 2 pronged attack can filter and block the major percentage of inbound robocalls