共查询到18条相似文献,搜索用时 171 毫秒
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基于多径路由协议,采用RS编码技术,设计了一种将数据信息编码后分片沿不同路径传输的方法,在目的节点对恶意篡改行为进行检测,确定恶意节点的具体位置或将恶意节点锁定在恶意节点组内.在此基础上提出了一个完整的抵制篡改数据攻击的信誉机制,充分利用了从数据传输和恶意节点检测过程中获得的信息,采用简单贝叶斯模型方法,对节点进行信誉评价,引入了恶意节点组的概念.数据在正常传输过程中无需重复加密和签名.实验表明,该信誉机制能够有机地与多径路由协议相结合,快速准确地孤立篡改数据的恶意节点. 相似文献
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数据融合传输算法在无线传感器网络中的应用 总被引:1,自引:1,他引:0
针对簇.树型的数据传输精确性提出一种算法.该算法是节点通过从基站接收到的话路密钥Kb与节点出厂时就设置的密钥Ki对感知数据进行加密,数据加密后使用密钥公式传送数据,可以进一步增强数据的精确性和完整性. 相似文献
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为了降低无线传感器网络数据间的冗余性,提高数据传输量和降低通信能耗,提出一种蝙蝠算法优化神经网络算法的数据融合策略.首先每个簇首节点接收该区域的各传感器节点检测到的数据,然后采用蝙蝠算法优化BP神经网络进行数据融合,最后采用仿真实验对其性能进行测试.仿真结果表明,本文算法节省了感知节点的能量消耗,延长了无线传感器网络的生命周期时间,提高数据融合的精度. 相似文献
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基于D-S证据理论的组合数据融合算法 总被引:4,自引:1,他引:3
针对在无线传感器网络中传感器节点本身能量有限的特性,提出一种基于D-S证据理论的组合数据融合算法.先对传感器网络的当前值依据各组数据的标准差进行聚类,然后对每一类数据组,用D-S证据推理算法进行融合,将其结果看成一个虚拟传感器节点数据,最后通过计算马哈诺比斯距离得出虚拟节点数据向量的异常值,把它作为加权权重进行加权融合.仿真试验表明:该算法识别目标的可信度高于D-S推理法,且在计算复杂度上也有明显优势. 相似文献
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基于数据融合的无线传感器网络路由算法 总被引:2,自引:0,他引:2
在分簇协议LEACH和链状协议PEGASIS的基础上,提出一种新的基于数据融合的分簇路由算法.簇首节点采用多跳方式传输数据,并根据周围节点的密集程度构造不同大小的簇;簇内节点计算上行和下行节点构造数据融合树,采用时分复用调度算法进行多跳路由.NS2仿真结果表明该路由算法均衡了各个节点的能量消耗,延长了网络存活时间,并降低了网络延迟. 相似文献
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给出了一种高效的无线多媒体传感器网络攻击检测和数据融合算法EIDSART。该算法从节点的多元属性方面对节点行为特征进行界定,通过选择合适的邻居节点集合,可以运用于任意规模的多媒体传感器网络;另外,在经过精确检测攻击行为的情况下,对传感数据进行了融合,降低了网络通信开销。仿真结果表明,EIDSART在攻击检测精度和误报率等方面具有优势,并能得到精确的数据融合结果。 相似文献
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针对某些特定场合无线传感器网络中传感器产生的数据时间和空间上的冗余和高度相关性,提出了一种面向数据相关性及权重的传感器网络采样优化算法DCACW。它基于聚合树结构连接整个网络,在各节点根据样本的相关性和节点权重进行数据融合。仿真实验结果表明,本算法采集的样本覆盖度更广,而且在聚合树中去除了冗余和相关的数据,保证了最终收集的样本差异性较强。 相似文献
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In order to avoid internal attacks during data aggregation in wireless sensor networks, a grid-based network architecture fit for monitoring is designed and the algorithms for network division, initialization and grid tree construction are presented. The characteristics of on-off attacks are first studied and monitoring mechanisms are then designed for sensor nodes. A Fast Detection and Slow Recovery (FDSR) algorithm is proposed to prevent on-off attacks by observing the behaviors of the nodes and computing reputations. A recovery mechanism is designed to isolate malicious nodes by identifying the new roles of nodes and updating the grid tree. In the experiments, some situations of on-off attacks are simulated and the results are compared with other approaches. The experimental results indicate that our approach can detect malicious nodes effectively and guarantee secure data aggregation with acceptable energy consumption. 相似文献
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Due to the openness of the cognitive radio network, spectrum sensing data falsification (SSDF) can attack the spectrum sensing easily, while there is no effective algorithm proposed in current research work, so this paper introduces the malicious users removing to the weight sequential probability radio test (WSPRT). The terminals' weight is weighted by the accuracy of their spectrum sensing information, which can also be used to detect the malicious user. If one terminal owns a low weight, it can be treated as malicious user, and should be removed from the aggregation center. Simulation results show that the improved WSPRT can achieve higher performance compared with the other two conventional sequential detection methods under different number of malicious users. 相似文献
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针对无线传感器网络数据汇聚与传输过程面临的安全威胁,文中提出一种基于安全数据汇聚与信息重构的多路由数据传输算法——MDT.该算法允许网络中存在妥协节点,也允许丢失部分数据.通过理论分析与仿真实验,证实该算法在不增加网络整体能耗的前提下,能有效地抵御侦听、数据篡改和拒绝服务攻击,全面提高系统的安全性和可靠性. 相似文献
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当今,车联网是实现智能交通应用的平台。车联网有着特殊的网络特征,使得其上的数据聚集算法不同现有的无线传感器网络数据聚集。数据聚集可以有效地降低传输过程中的数据量,但同时亦会引起数据时延的增加和数据精度的降低。因此聚集算法往往考虑聚集数据的时延和精度。本文对现有的车联网聚集算法进行综述分析。 相似文献
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Rahim Khan Muhammad Zakarya Zhiyuan Tan Muhammad Usman Mian Ahmad Jan Mukhtaj Khan 《International Journal of Communication Systems》2019,32(18)
Heterogeneous wireless sensor networks (WSNs) consist of resource‐starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy‐efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application‐specific or too complex that make their implementation unrealistic, specifically, in a resource‐constrained environment. In this paper, we propose a novel node‐level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in‐network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real‐time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay. 相似文献
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针对现有隐私保护数据聚集算法依赖某种网络拓扑结构和加解密次数过多的问题,本文提出了一种基于同心圆路线的隐私保护数据聚集算法PCIDA (Privacy-preserving and Concentric-circle Itinerary-based Data Aggregation algorithm).PCIDA沿着设计好的理想路线执行数据聚集,使得算法不依赖网络拓扑结构.PCIDA利用安全通道保证数据的隐私性,避免了数据聚集过程中的加解密运算.PCIDA沿着同心圆并行处理,使得算法数据处理延迟较小.理论分析和实验结果显示,PCIDA在较低通信量和能耗的情况下获得较高的数据隐私性和聚集精确度. 相似文献