| 摘要 |
<P>PROBLEM TO BE SOLVED: To provide embodiments for detecting anomalous consumption of energy. <P>SOLUTION: Information associated with energy consumption over a designated period of time is received. A threshold value is received. A classifier based on an autoregressive moving average model is applied to the information and a result representing the likelihood of an attack is determined. The result is then analyzed to determine if it attained a threshold value. The information is then classified as indicating an attack. Additionally, embodiments for utilizing machine learning to train the classifier using training data to develop parameters for the autoregressive moving average model are provided. Further, embodiments for evaluating the effectiveness of the parameters used in the autoregressive moving average model to classify data are provided. <P>COPYRIGHT: (C)2013,JPO&INPIT |
