DPI and Content Filtering

Protect your revenue with Traffic Classifier

“The time to fix the roof is when the sun is shining”
so said JFK. 

Don’t plan for revenue protection after the event – the challenge for the operator is to have the flexible software tools in place ready to handle changing weather conditions.

It’s time to reboot DPI and traffic analysis from a fixed appliance to a next generation agile software tool – now, while the sun is shining.

There are a number of key revenue threats that can affect operator networks; but primarily these are due to users having access to unauthorized services, bypassing existing controls. Accurate deep packet inspection and enforcement is the dynamic software tool required to identify, intercept and block this activity.

Examples of revenue threat from a network perspective:

  • Domain Fronting - where a domain appears to be one service but is, in-reality, another. This is a common way for users to get access to unauthorized content for their plan
  • SIMBox Fraud – bypassing interconnect call charges via VOIP routing and local breakout
  • Unauthorised VPN – users using VPN apps to bypass content access controls for their plan
  • Activity enforcement – a user plan which allows Chat but not VOIP for social network

Openwave's cloud native Traffic Classifier DPI solution enables these threats and new risks to be analysed with thousands of protocol and meta data options.

OurTraffic Classifier uses the industry leading Qosmos ixEngine as a basis for the widest and most accurate embedded deep packet inspection & classification available today. Qosmos ixEngine is embedded in diverse range of telecom equipment from GGSN to router to firewall; providing a complete view of the traffic path.

The deep packet inspection & traffic enforcement combines with traffic analytics to provide the dynamic capability to analyse what is happening with application and protocol traffic at multiple levels. The easy to use at GUI enables creation of dynamic traffic queries for key user data generated per flow / session, filtering by multiple vectors including  location, time, category, device, protocol on the mobile data access flows. The session information and network data provides an extensive set of meta to correlate analysis of consumption, app and protocol.

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Using this sophisticated traffic analysis enables patterns of usage to be better understood, new application changes to be highlighted and any ‘Unknowns’ to be resolved quickly.




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