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| 基于加权拟合分析的WSN安全数据融合机制研究 |
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李平1,2, 阳武1, 谢晋阳1, 朱红松2, 张永光1, 李晓锋3
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1.长沙理工大学 计算机与通信工程学院, 湖南 长沙 410114;2.中国科学院 信息工程研究所 信息安全国家重点实验室, 北京 100093;3.北京控制工程研究所 软件研制中心, 北京 100190
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| 摘要: |
| 传统的基于密码学方式的安全机制并不能有效解决妥协节点产生的假冒攻击问题,同时,基于簇头的信任判断和证实机制需要更多的通信开销,使得基于簇头的信任管理与认证是当前安全数据融合机制研究的焦点.以能量衰减模型的事件感知为研究场景,设计一种基于加权拟合分析的安全数据融合机制.在事件源情况未知的条件下,实现簇内节点对事件源距离的近似估计.研究具有簇属性特征的数据点基于所拟合曲线的分布性质,提出基于曲线簇分析的簇头信任判断机制.仿真实验结果表明,所提出的机制在曲线拟合精度、防妥协性能等方面有较高的提升,达到了预期的效果. |
| 关键词: 数据融合 加权曲线拟合 无线传感器网络 安全 |
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| 基金项目:国家高技术研究发展计划(863)(2013AA014002); 国家重点基础研究发展计划(973)(2011CB302902); 中国科学院信息工程研究所前瞻部署项目(Y3Z0071G02) |
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| Study on Mechanisms of Secure Data Aggregation Based on Weighted Fitting Analysis |
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LI Ping1,2, YANG Wu1, XIE Jin-Yang1, ZHU Hong-Song2, ZHANG Yong-Guang1, LI Xiao-Feng3
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1.School of Computer and Telecommunications, Changsha University of Science and Technology, Changsha 410114, China;2.State Key Laboratory of Information Security, Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;3.Software Development Center, Beijing Institute of Control Engineering, Beijing 100190, China
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| Abstract: |
| Cryptographic approaches are vulnerable to impersonation attacks when nodes become compromised. Meanwhile, trust-based judgment and confirmation of cluster heads in WSN imposes higher communication cost. Trust management and authentication on cluster heads in WSN are essential in research on the mechanisms of secure data aggregation at present. In this paper, an energy attenuation model is adopted to describe event sensing in a kind of WSNs. Approximate evaluation on distance between occurring event and nodes within a cluster is achieved in case the location of the event is not known. Distribution properties of data points with clustering characteristics based on fitting curve construction are theoretically analyzed. In addition, the mechanism on trust authentication on cluster heads is also refined. Experimental results show that the proposed mechanism has much better performance on fitting accuracy and malicious CH recognition than previous works. |
| Key words: data aggregation weighted fitting curve WSN security |
