1. Snapp, S.R., Brentano, J., Dias, G.V., Goan, T.L., Heberlein, L.T., Ho, C., Levitt, K.N., Mukherjee, B., Smaha, S.E., Grance, T., Teal, D.M., Mansur, D.: DIDS (Distributed Intrusion Detection System) Motivation, Architecture, and An Early Prototype. In: Proc. 14th National Computer Security Conference (1991)
2. Eskin, E., Arnold, A., Prerau, M., Portnoy, L., Stolfo, S.: A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. In: Applications of Data Mining in Computer Security, Kluwer, Dordrecht (2002)
3. Portnoy, L., Eskin, E., Stolfo, S.: Intrusion Detection with Unlabeled Data using Clustering. In: Proc. Workshop on Data Mining for Security Applications (2001)
4. Hofmeyr, S., Forrest, S.: Architecture for an Artificial Immune System. Evolutionary Computation 7(1), 1289–1296 (1999)
5. Mahoney, M., Chan, P.: Learning Nonstationary Models of Normal Network Traffic for Detecting Novel Attacks. In: Proc. 8th ACM KDD (2002)