A fusion approach for anomaly detection in hard disk drives

Abstract

As the information stored in hard disk drives (HDDs) is continuous increasing, the safety of data is become more and more important. Among the safety technologies, anomaly detection is crucial for users to prevent data loss and to backup their data. A fusion approach was proposed to monitor the HDD health status based on Mahalanobis distance (MD) and Box-Cox transformation. A quality control technique-Shewhart control chart-was introduced using the transformed MD values to detect the anomalies in HDDs. A case study was then conducted to verify the validity of the proposed approach. The results showed that the proposed approach is effective for detecting the anomalies.