University of California

Sprint Communications Comapny L.p.

Deutschetelekom Ag

Narus, Inc.

Chen-Nee Chuah

Antonio Nucci

Hui Zang

Jatinder Pal Singh

Sara Gatmir-Motahari

Srinivasan Seetharaman

Guanyao Huang

Soon-Tee Teoh

Han Liu

Saqib Raza

Systems, methods and computer-readable media for detecting potential data fraud in a telecommunications environment are provided. The methods include referencing a characteristic associated with a device, where the characteristic provides an indication of a device type for a device. From the referenced characteristic, a device type is predicted. A comparison is made between the predicted device type and an expected device type that is identified based on the credentials being used by the device. Thereafter, a determination that the device is potentially performing data fraud can be made based on whether predicted device type matches the expected device type.

Data fraud detection via device type identification

A method for routing-assisted traffic monitoring includes providing a set of flows, each flow having an associated ingress routing device and an associated egress routing device. A controller determines a micro-flowset routing for the set of flows, the micro-flowset routing defining which of a set of directed links connecting a plurality of routing devices are used to route each of the flows from the respective ingress routing device to the respective egress routing device. The controller transmits flow information to at least a first routing device of the plurality of routing devices according to the micro-flowset routing, the flow information defining which of the set of directed links are to be used to route at least one flow entering the first routing device to a second routing device of the plurality of routing devices.

Method for routing-assisted traffic monitoring

The present invention comprises a multi-tier system. Major goals of the system are to 1) clearly visualize BGP dynamics and alert/report important deviation of BGP dynamics to avoid overwhelming the operators with too much information and 2) analyze the root cause of the problems by using a multi-tier approach, with a light-computational analysis and high-level classification for a real-time problem identification followed by a more rigorous off-line analysis for a further and more detailed trouble shooting. An example embodiment is provided that comprises four modules. The first module comprises a distributed family of collectors in charge of collecting real-time network information. The second module filters out non-relevant prefixes and extracts and profiles key features of the network information. The third module monitors BGP activity from both an Internet-AS and single-AS perspectives by displaying the data in real time and highlighting major shifts or divergence from historical baselines with comprehensive layouts. The forth module is run off-line to focus on a few relevant events that are selected through the first three modules. This is usually a time-consuming phase of the process due to the different temporal and/or spatial correlation that must be run across several sets of data. During this phase, the system can spend more time to better identify the real cause of the problem.

Method for real-time visualization of BGP analysis and trouble-shooting

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Davis, CA, United States of America

Chen-Nee Chuah