共查询到20条相似文献,搜索用时 140 毫秒
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目前,网络入侵技术越来越先进,许多黑客都具备反检测的能力,他们会有针对性地模仿被入侵系统的正常用户行为;或将自己的入侵时间拉长,使敏感操作分布于很长的时间周期中;还可能通过多台主机联手攻破被入侵系统.对于伪装性入侵行为与正常用户行为来说,仅靠一个传感器的报告提供的信息来识别已经相当困难,必须通过多传感器信息融合的方法来提高对入侵的识别率,降低误警率.应用基于神经网络的主观Bayes方法,经实验,效果良好. 相似文献
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入侵检测是用来发现网络外部攻击与合法用户滥用特权的一种方法。数据挖掘技术是一种决策支持过程。它能高度自动化地分析原有的数据 ,做出归纳性的推理 ,从中挖掘出潜在的模式 ,预测出客户的行为。根据数据挖掘技术在入侵检测中的应用情况 ,可采用关联规则技术实地建立了一个网络行为模式规则库 相似文献
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无线传感器网络由大量节点组成,网络面临的问题很难全部被仿真工具描述,因而由仿真得到的无线传感器网络应当在部署之前进行物理测试.根据无线传感器网络节点的一般架构,设计完成了一批体积小、成本低、功耗低、硬件资源丰富和代码开源的无线传感器节点,组建了一个无线传感器网络实验平台.在平台上移植了Contiki操作系统管理节点的软硬件资源,设计实现了射频芯片、串行接口和温度传感器的驱动程序.采用6LowPAN协议构建自组织网络,验证了平台的节点通信半径和组网效果.试验表明该平台完整支持6LowPAN协议,采集数据的可靠性、网络的健壮性和通信半径等指标,可以满足无线传感器网络节点定位与环境变量检测等应用的需求. 相似文献
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利用无线传感器网络及Zigbee协议标准,对押运信息感知监测系统进行了分析;提出了基于Zigbee无线传感器网络与空间定位技术、计算机技术、数据通信技术结合的押运信息感知监测系统架构;设计了押运感知监测网络中感知节点的软硬件,并且对网络感知节点软硬件功能进行了测试。 相似文献
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一种基于生物免疫原理的入侵检测新模型 总被引:1,自引:0,他引:1
入侵检测系统可以从生物免疫系统的很多特点中得到启发,文中利用生物免疫原理设计了一个新的入侵检测框架模型,该框架在传统信息传输网基础上构建了免疫淋巴网,用来监控和管理传统传输网的行为。模型中还应用了阴性选择、克隆选择等免疫算法,使得该模型对于入侵检测问题有较好的敌我识别功能。 相似文献
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基于聚类技术提出了一种能处理不带标识且含异常数据样本的训练集数据的网络入侵检测方法。对网络连接数据作归一化处理后 ,通过比较数据样本间距离与类宽度W的关系进行数据类质心的自动搜索 ,并通过计算样本数据与各类质心的最小距离来对各样本数据进行类划分 ,同时根据各类中的样本数据动态调整类质心 ,使之更好地反映原始数据分布。完成样本数据的类划分后 ,根据正常类比例N来确定异常数据类别并用于网络连接数据的实时检测。结果表明 ,该方法有效地以较低的系统误警率从网络连接数据中检测出新的入侵行为 ,更降低了对训练数据集的要求。 相似文献
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无线传感器网络的能量消耗是空间不均匀的,但当前多数的部署方法考虑得较少,网络的能量利用率低,因此提出了保证覆盖率和网络生存期的最少节点部署问题.基于传感器网络的数据传输特性,从提高能量效率和降低剩余能量的角度提出了节点数递减的重叠放置方法和节点密度递减的随机部署方法.两种新部署方法比已有部署方法需要的节点数少,剩余能量低,因而提高了能量利用率.最后,仿真实验表明,两种新部署策略的能量效率是已有方法的3~4倍. 相似文献
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由于无线传感器网络在能量消耗、内存开销和计算能力等方面的局限性,传统的网络密钥管理方法已不适用。为此提出了一种适用于无线传感器网络的密钥预分配方法——基于(t,n)-门限方案,给出了密钥分配方法,并从方案的连通性、安全性等方面进行了有效的分析,结果表明该算法在这些方面有一定的优势。 相似文献
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This paper mainly studied the problem of energy conserving in wireless sensor networks for target tracking in defensing combats. Firstly, the structures of wireless sensor nodes and networks were illustrated; Secondly, the analysis of existing energy consuming in the sensing layer and its calculation method were provided to build the energy conserving objective function; What's more, the other two indicators in target tracking, including target detection probability and tracking accuracy, were combined to be regarded as the constraints of the energy conserving objective function. Fourthly, the three energy conserving approaches, containing optimizing the management scheme, prolonging the time interval between two adjacent observations, and transmitting the observations selectively, were introduced; In addition, the improved lion algorithm combined with the Logistic chaos sequence was proposed to obtain sensor management schemes. Finally, simulations had been made to prove the effectiveness of the proposed methods and algorithm. 相似文献
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《防务技术》2020,16(3):737-746
Infrared target intrusion detection has significant applications in the fields of military defence and intelligent warning. In view of the characteristics of intrusion targets as well as inspection difficulties, an infrared target intrusion detection algorithm based on feature fusion and enhancement was proposed. This algorithm combines static target mode analysis and dynamic multi-frame correlation detection to extract infrared target features at different levels. Among them, LBP texture analysis can be used to effectively identify the posterior feature patterns which have been contained in the target library, while motion frame difference method can detect the moving regions of the image, improve the integrity of target regions such as camouflage, sheltering and deformation. In order to integrate the advantages of the two methods, the enhanced convolutional neural network was designed and the feature images obtained by the two methods were fused and enhanced. The enhancement module of the network strengthened and screened the targets, and realized the background suppression of infrared images. Based on the experiments, the effect of the proposed method and the comparison method on the background suppression and detection performance was evaluated, and the results showed that the SCRG and BSF values of the method in this paper had a better performance in multiple data sets, and it’s detection performance was far better than the comparison algorithm. The experiment results indicated that, compared with traditional infrared target detection methods, the proposed method could detect the infrared invasion target more accurately, and suppress the background noise more effectively. 相似文献