首页> 外文期刊>Eurasip Journal on Wireless Communications and Networking >Scaling of wireless sensor network intrusion detection probability: 3D sensors, 3D intruders, and 3D environments
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Scaling of wireless sensor network intrusion detection probability: 3D sensors, 3D intruders, and 3D environments

机译:无线传感器网络入侵检测概率的扩展:3D传感器,3D入侵者和3D环境

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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. Keywords WSN WSN security Intrusion detection QoS 3D sensor applications
机译:在本文中,提出了一种在3D无线传感器网络(WSN)中部署异构传感器的新模型。该模型处理两种传感方案:单传感和多传感。比较了使用高斯,均匀,β和卡方分布的传感器在3D环境中进行入侵检测的可能性。结果概率值可帮助WSN安全设计人员针对某些关键网络参数(例如服务质量(QoS))选择最合适的传感器部署。还展示了在不同概率分布下的WSN效率。为了评估提出的模型,使用OPNET和NS2构建了一个仿真环境。仿真结果表明,高斯分布提供了最佳的效率和性能。关键词WSN WSN安全入侵检测QoS 3D传感器应用

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