A dynamic compuation approach to determining the threshold in network anomaly detection

作者：Yu Yan Hua^*; Song Mei Na; Zhang Wen Ting; Song Jun De

来源：Journal of Beijing University of Posts and Telecommunications, 2011, 34(2): 45-49.

• Anomaly detection
• Auto-regressive integrated moving average
• Communication networks
• Confidence degree
• Confidence interval
• Network anomalies
• Network anomaly detection
• Performance degradation
• Seasonal autorgressive integrated moving average
• Statistical hypotheses testing
• T distribution
• Time series prediction
• White noise process

Fault correction by detecting anomalies designating performance degradation is an important approach to improving the reliability of communication network. Statistical hypotheses testing approach is employed to detect network anomaly. A new approach to acquiring the fluctuation threshold is proposed comprehensively when taking advantage of time series prediction confidence interval computation based on multiplicative autoregressive integrated moving average. Furthermore, under the assumption that the training residual which is a white noise process follows normal distribution, the associated confidence interval of prediction can be figured out under any given confidence degree by constructing random variable satisfying t distribution. Experiments verify the effectiveness of anomaly detection mechanism and the accuracy of the algorithm.

• 出版日期2011
• 单位北京大学