Anomaly detection in transactional sequential data

作者：Zhang Jingwei; Lin Yuming; Zhang Huibing; Yang Qing^*

来源：Information Technology Journal, 2012, 11(7): 782-787.

DOI：10.3923/itj.2012.782.787

• Anomaly detection
• Different distributions
• Distance metrics
• Distribution distance
• Response signal
• Sequential data
• System change
• Transactional systems

A transactional system often has a steady distribution based on their decisions or responses on various transactions. If the system is changed, the distribution also often changes. It is a valuable work to detect anomaly caused by system changes based on different distributions. In this study, we modeled those decision or response signals into a series of time-related distributions and then proposed a method combining distance metrics and anomaly detection to discover whether changes have happened in some systems. Distance metrics on different distributions can decide whether changes have happened and anomaly detection can find what happened further. Extensive experiments show that our method has a good performance and can locate the anomaly accurately.

• 出版日期2012