METHOD OF DETECTING ANOMALIES SUSPECTED OF ATTACK, BASED ON TIME SERIES STATISTICS
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United States of America Patent
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Jul 28, 2016
app pub date -
Mar 5, 2015
filing date -
Jan 28, 2015
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Disclosed is a method of detecting anomalies suspected of an attack based on time series statistics according to the present invention. The method of detecting anomalies suspected of an attack according to the present invention includes the steps of: collecting log data and traffic data in real-time and extracting at least one piece of preset traffic feature information from the collected log data and traffic data; and training through a time series analysis-based normal traffic training model using the extracted traffic feature information, and detecting abnormal network traffic according to a result of the training.
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