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In this paper, a new model that deploys heterogeneous sensors in 3D wireless sensor networks (WSNs) is proposed. The model handles the two sensing scenarios, single sensing and multiple sensing. The probabilities of intrusion detection in a 3D environment with sensors distributed using Gaussian, uniform, beta, and chi-square are compared. The resultant probabilities values help the WSN security designers in selecting the most suitable sensors deployment regarding some critical network parameters such as quality-of-service (QoS). WSN efficiency under different probabilistic distributions is also demonstrated. To evaluate the proposed model, a simulation environment is constructed using OPNET and NS2. The simulation results showed that Gaussian distribution provides the best efficiency and performance.

Scaling of wireless sensor network intrusion detection probability: 3D sensors, 3D intruders, and 3D environments