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This paper investigates the asymmetric costs of false errors to enhance the detection systems performance. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of probe detection is enhanced by considering the costs of false errors.

The network model for Detection Systems based on data mining and the false errors