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中文摘要：
融合了密码学、经济学、统计学、数据分析等相关领域的知识来建立可信传感器网络,探讨了一种基于高斯分布的传感器网络信誉模型（GRFSN,Gauss reputation framework for sensor network）描述方法。通过对高斯概率分布与信誉分布的拟合分析与证明,证实了用高斯分布建立信誉模型的途径是可行的。通过仿真实验,说明了高斯分布可更好地保持信誉稳定性和表达信任更加直观等特点,实验也显示了GRFSN模型具有更强的识别故障和抵御信誉恶意攻击能力的优越性。
英文摘要：
Knowledge from relative domains such as cryptography, economics, statistics, and data analysis was combined together for the development of trustworthy sensor networks, a Gaussian reputation framework for sensor networks （GRFSN） was proposed, which was developed by JOsang＇s opinion, with the fitting analyses and test between Gaussian probability distribution and reputation distribution, the possibility to develop reputation model using Gaussian distribu- tion has been proved. Through some preliminary simulation results, this framework is more stabile to describe reputation against other distributions and easier to express the trust directly, and it also has the powerful ability to prevent from malicious attacks or faulty nodes.
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