User Entity Behavioral Analytics (UEBA) has made a noticeable impact in the generic threat detection community. While UEBA has made its way into SIEM Log Management platforms, endpoint protection and the cloud access security brokers, real-time communications environments are still greatly underserved. With the wide varieties and inherent complexities of SIP and VoIP protocols, RTC environments can only stand to benefit from the added value of behavioral analytics and machine learning. Specific to the RTC environment, behavior analysis combined with machine learning 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.
Features & Benefits
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