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Everyone knows the services of the Internet. Internet services contain large scale of data. Security is one of the important issues during transmission of data over the network. To avoid misuse of data an efficient Network Intrusion Detection Systems (NIDS) is needed. To predict intrusion over the network a combined features of Dendritic Cell Algorithm (DCA) and Dempster Belief Theory (DBT) has been used called hybrid model of DCA and DBT. This algorithmic approach comes under the Artificial Immune Detection System. The presented system is about to analyze the network statistics under different parameters and identify the False Negative Rate and the Uncertainty Parameters. Based on these parameters analysis, the intrusion will be identified. The work is about to decrease the False Positive and False Negative rates so that the more effective intrusion detection will be performed.

Dendritic Cell Algorithm and Dempster Belief Theory Based Approach for Intrusion Detection System