Determining usage predictions and detecting anomalous user activity through traffic patterns
First Claim
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1. A method of detecting anomalies in the data traffic of a mobile device, comprising the steps of:
- collecting at a server and from the mobile device, data traffic statistics for a given time period;
comparing the data traffic statistics against threshold values;
if a statistic of the data traffic statistic exceeds a corresponding threshold of the threshold values, flagging an anomaly;
updating the threshold values based on a running average of each statistic of the data traffic statistics based on formula I,
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Abstract
The present invention concerns a system for selecting and monitoring data plans for telecommunications systems, and methods of determining, learning and estimating usage patterns in-order to predict usage and tie this to cost and the overlaying of plan selection for cost optimization. Further, additional methods are applied to determine anomalous user behaviors and raise security and data leakage related events.
17 Citations
14 Claims
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1. A method of detecting anomalies in the data traffic of a mobile device, comprising the steps of:
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collecting at a server and from the mobile device, data traffic statistics for a given time period; comparing the data traffic statistics against threshold values; if a statistic of the data traffic statistic exceeds a corresponding threshold of the threshold values, flagging an anomaly; updating the threshold values based on a running average of each statistic of the data traffic statistics based on formula I, - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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Specification