1. Hawkins, D. M. (1980). Identification of outliers. London: Chapman and Hall.
2. Eskin, E., Arnold, A., Prerau, M., Portnoy, L., & Stolfo, S. (2002). A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data. In: Barbará, D., & Jajodia, S. (Eds.), Applications of data mining in computer security. Advances in Information Security (Vol. 6, pp. 77–101).
3. Lane, T., & Brodley, C. E. (1998). Temporal sequence learning and data reduction for anomaly detection. In Proceedings of the 1998 5th ACM Conference on Computer and Communications Security (CCS-5), San Francisco, CA, USA (pp. 150–158).
4. Bolton, R. J., & David, J. H. (2002). Unsupervised profiling methods for fraud detection. Statistical Science, 17(3), 235–255.
5. Wong, W., Moore, A., Cooper, G., & Wagner, M. (2002). Rule-based anomaly pattern detection for detecting disease outbreaks. In Proceedings of the 18th National Conference on Artificial Intelligence, Edmonton, Alta., Canada (pp. 217–223).