@article{(Open Science Index):https://publications.waset.org/pdf/13410, title = {Intrusion Detection based on Distance Combination}, author = {Joffroy Beauquier and Yongjie Hu}, country = {}, institution = {}, abstract = {The intrusion detection problem has been frequently studied, but intrusion detection methods are often based on a single point of view, which always limits the results. In this paper, we introduce a new intrusion detection model based on the combination of different current methods. First we use a notion of distance to unify the different methods. Second we combine these methods using the Pearson correlation coefficients, which measure the relationship between two methods, and we obtain a combined distance. If the combined distance is greater than a predetermined threshold, an intrusion is detected. We have implemented and tested the combination model with two different public data sets: the data set of masquerade detection collected by Schonlau & al., and the data set of program behaviors from the University of New Mexico. The results of the experiments prove that the combination model has better performances. }, journal = {International Journal of Computer and Information Engineering}, volume = {1}, number = {7}, year = {2007}, pages = {1953 - 1961}, ee = {https://publications.waset.org/pdf/13410}, url = {https://publications.waset.org/vol/7}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 7, 2007}, }