An Ontology Development for Anomaly Detection in File Integration Domain

Nowadays, there has been an enormous increase in the variety of data storage and software development technologies. Integration and diversity in collaborative organizations emerge as a fundamental problem due to the rapidly evolving and changing technologies. In this context, file integration comes out as an effective solution in order to integrate data between different business platforms. Thus, routine business processes and business logic of different electronic systems could be automated. Anomaly detection is a data analysis process that detects abnormal situations in systems. Anomaly detection provides an awareness for the unexpected situations in information based systems and the fulfillment of necessary actions against anomalies that do not comply with the expected behavior. Therefore, anomaly detection is an important data analysis process to detect anomalies that occur in file integrations. In this study, an ontology based approach is presented in order to detect anomalies in file integration systems. Anomaly detection in file integrations is important in terms of availability which is one of the component of information security triad (confidentiality, integrity, availability). Most of the anomalies in integrations are oriented to data integrity and these anomalies can be detected from the transfer time or the incoming file size. In the proposed ontological approach, the file integrations made to a sample system are being queried and anomalies that occur in the integration processes are being detected. The proposed approach is intended to provide an ontology-based solution to data integrity and availability (anomalies that can stop the file flow) in the file integration systems