Dendritic Cells Algorithm （DCA） is a new development in Artificial Immune System （AIS）. It has various parameters, and as yet has not been ex- tensively tested. The general applicability of the al- gorithm to a va...Dendritic Cells Algorithm （DCA） is a new development in Artificial Immune System （AIS）. It has various parameters, and as yet has not been ex- tensively tested. The general applicability of the al- gorithm to a variety of problems is d. The aim of this work is to demonstrate the feas^ility and ro- bustness of the algorithm, and the sensitivity to the change of various parameters in a series of experi- ments for Nmap portscan detection by using DCA. Experiment results show that the algorithm per- forms well on the task of detecting a ping based Nmap portscan. Sensitivity analysis is also per- formed. True positive rate is higher for the detec- tion of anomaly processes and false positive rate is lower for the detection of normal orocesses.展开更多
Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical...Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated. Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the 搒wing points? And such points may leak out more information for data analysts.展开更多
基金supported by the National Natural Science Foundation of China under Grants No.61100205,No.60873001the Project 2009RC0212 of the Fundamental Research Funds for the Central Universities
文摘Dendritic Cells Algorithm （DCA） is a new development in Artificial Immune System （AIS）. It has various parameters, and as yet has not been ex- tensively tested. The general applicability of the al- gorithm to a variety of problems is d. The aim of this work is to demonstrate the feas^ility and ro- bustness of the algorithm, and the sensitivity to the change of various parameters in a series of experi- ments for Nmap portscan detection by using DCA. Experiment results show that the algorithm per- forms well on the task of detecting a ping based Nmap portscan. Sensitivity analysis is also per- formed. True positive rate is higher for the detec- tion of anomaly processes and false positive rate is lower for the detection of normal orocesses.
文摘Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated. Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the 搒wing points? And such points may leak out more information for data analysts.
