# Anomaly Detection for Service-Oriented Business Processes Using Conformance Analysis
## 1 Introduction  
Business processes in service-oriented organisations are managed by their service management systems, which are responsible for systematising offered services in the form of business processes [1]. These management systems are also responsible for executing business processes in the most effective manner so that customers (both internal and external) receive the best services possible. Service-related business processes are the direct interaction links between an organisation and its service recipients, such as healthcare services interacting with patients and physicians, banking services interacting with their customers, and telecommunications services interacting with their clients. The data generated during the execution of these processes is used to analyse and enhance their execution. The objective of such an analysis is to enhance the quality of the customer experience, thereby increasing the competitive advantage of the business and contributing directly to its success. Over the last few decades, corporations have become increasingly competitive in their pursuit of regulatory compliance. There has been a continuous interest in research for business process improvement, particularly in forecasting business process outcomes and their implications on process improvement. Businesses must predict the expected outcomesof business processes with the utmost degree of precision possible. Early prediction can have a significant impact on customers' satisfaction with the services they are receiving [2]. The biggest challenge for organisations is the timely identification of the abnormalities or deviations in their process executions. These deviations from the usual process execution may result in the inability to achieve the desired business objectives driven by the process. Failure to execute a process could be caused by a number of factors, the identification of which requires a thorough investigation and root cause analysis. On the other hand, the success criteria of any process could be dependent on a variety of elements, such as the prompt completion of an order and delivery for an online purchase process. In other words, the process is executed successfully when its services' objectives are met, and vice versa. Process mining techniques enable organisations to gain insight into their processes by utilising the event data captured by services management systems. A process is a collection of discrete activities or events designed to achieve a particular business objective. Process mining techniques are focused on three main areas: (i) process discovery, dealing with the discovery of the process models based on the behaviour of events [3], (ii) conformance analysis, identifying inconsistencies between actual process executions and behaviour of the process observed through the discovered process model [4], and (iii) process enhancement, establishing a feedback mechanism for the improvement of the process model through the learning of conformance analysis. Once a process model is discovered, conformance checking apprehends the reality of synchronisation between the recorded logs and the discovered model. Customer-centric organisations are focused on using the collected data to measure the conformance of their business processes. This is one of the ways to make sure that their service level is up to the standards for customer satisfaction. We further explored the conformance checking techniques in this work to identify, spot on and classify the anomalies and their severity in the execution of the business process. Furthermore, customer-centric organisations use service management systems that interact with their customers and execute the business processes. This execution generates a large amount of data as events in the executing process are recorded by the system and these data are used for gauging the performance of the process.