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This paper introduces a novel deployment strategy to leverage the advantages of both Poisson and Gaussian distributions in random sensor deployment for intrusion detection. The basic idea is to employ multiple deployment points in the area of interest. How to choose the number and locations of the k deployment points for optimizing the network performance under given network investment is therefore a must-answer question. This paper theoretically and experimentally explores the problem under multi-level sensing and detection model. Simulation outcomes are shown to match very well with the theoretical results and validate the effectiveness of the proposed approach and the correctness of the modeling and analysis. This work provides insight on choosing the appropriate number of deployment points and their placement for efficient intrusion detection given arbitrary application requirements.