Many corporations worldwide use an enterprise resource planning (ERP) system to manage their business process, which continuously changes due to dynamic business requirements [1]. Because the processes run continuously, ERP produces a considerable log of processes. Manual observation will have difficulty monitoring the sizeable log, especially detecting anomalies. It needs the method that can detect anomalies in the huge log. Standard business processes are usually incorporated into standard operating procedures (SOP), which are used as a reference to find any deviations. Deviations or anomalies in the business process can be caused by variations or operation errors [2]; however, some of the anomalies may be the result of fraudulent behaviours [3]. Fraud can be committed in many ways and can lead to significant losses. In 2012, the Association of Certified Fraud Examiners (ACFE) reported that there had been 1.388 fraud cases in 96 countries, which have incurred US$1.4 billion in losses [4]. On average, organizations
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