Methodologies and systems for detecting an anomaly in a flow of data or
data stream are described herein. To detect an anomaly, an anomaly
detection server may create a baseline based on historical or other known
non-anomalous data within the data stream. The anomaly detection server
then generates one or more test values based on current data in the data
stream, and compares the test value(s) to the baseline to determine
whether they vary by more than a predetermined amount. If the deviation
exceeds the predetermined amount, an alarm is triggered. The anomaly
detection server may continually adjust the baseline based on the current
data in the data stream, and may renormalize the baseline periodically if
desired or necessary.