In order to avoid lots of holes among mature immune detectors and deal with the problem of boundary invasion in intrusion detection, analyzing the relationship between number of detectors and detection performance, a detector distribution optimization algorithm with Monte Carlo estimation was proposed: evaluating the coverage of detectors by the Monte Carlo method, and updating the detector set by the offspring to improve detectors' distribution. The experimental tests demonstrate that the algorithm can not only decrease the holes but also achieve a more precise coverage of the nonself space with fewer detectors, and increase the detector's detection performance.