Key-insulated encryption based group key management for wireless sensor network

The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key management scheme is responsible for secure distributing group keys among valid nodes of the group. Based on the key-insulated encryption (KIE), we propose a group key management scheme (KIE-GKMS), which integrates the pair-wise key pre-distribution for WSN. The KIE-GKMS scheme updates group keys dynamically when adding or removing nodes. Moreover, the security analysis proves that the KIE-GKMS scheme not only obtains the semantic security, but also provides the forward and backward security. Finally, the theoretical analysis shows that the KIE-GKMS scheme has constant performance on both communication and storage costs in sensor nodes.

A target group tracking algorithm based on a hybrid sensor network

Traditional tracking algorithms based on static sensors have several problems. First, the targets only occur in a part of the interested area; however, a large number of static sensors are distributed in the area to guarantee entire coverage, which leads to wastage of sensor resources. Second, many static sensors have to remain in active mode to track the targets, which causes an increase of energy consumption. To solve these problems, a target group tracking algorithm based on a hybrid sensor network is proposed in this paper, which includes static sensors and mobile sensors. First, an estimation algorithm is proposed to estimate the objective region by static sensors, which work in low-power sensing mode. Second, a movement algorithm based on sliding windows is proposed for mobile sensors to obtain the destinations. Simulation results show that this algorithm can reduce the number of mobile sensors participating in the tracking task and prolong the network lifetime.

A target group tracking algorithm for wireless sensor networks using azimuthal angle of arrival information

In this paper, we explore the technology of tracking a group of targets with correlated motions in a wireless sensor network. Since a group of targets moves collectively and is restricted within a limited region, it is not worth consuming scarce resources of sensors in computing the trajectory of each single target. Hence, in this paper, the problem is modeled as tracking a geographical continuous region covered by all targets. A tracking algorithm is proposed to estimate the region covered by the target group in each sampling period. Based on the locations of sensors and the azimuthal angle of arrival （AOA） information, the estimated region covering all the group members is obtained. Algorithm analysis provides the fundamental limits to the accuracy of localizing a target group. Simulation results show that the proposed algorithm is superior to the existing hull algorithm due to the reduction in estimation error, which is between 10% and 40% of the hull algorithm, with a similar density of sensors. And when the density of sensors increases, the localization accuracy of the proposed algorithm improves dramatically.

An Adaptive Key Management Framework for the Wireless Mesh and Sensor Networks

Wireless sensor networks (WSNs) and wireless mesh networks (WMNs) are popular research subjects. The interconnection of both network types enables next-generation applications and creates new optimization opportunities. Currently, plenty of protocols are available on the security of either wireless sensor networks or wireless mesh networks, an investigation in peer work underpins the fact that neither of these protocols is adapt to the interconnection of these network types. The internal cause relies on the fact that they differ in terms of complexity, scalability and network abstraction level. Therefore, in this article, we propose a unified security framework with three key management protocols, MPKM, MGKM, and TKM which are able to provide basic functionalities on the simplest devices and advanced functionalities on high performance nodes. We perform a detailed performance evaluation on our protocols against some important metrics such as scalability, key connectivity and compromise resilience, and we also compare our solution to the current keying protocols for WSNs and WMNs.

Group Target Tracking in WSN Based on Convex Hulls Merging

When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.

无线传感网络混合密钥安全分簇方法

无线传感网络安全性在很大程度上依赖簇首,对该节点的维护和分配对其安全性具有重要意义。为此,基于混合密钥分配提出了一种无线传感网络安全分簇方法。该方法在建立无线传感网络模型和攻击者模型的基础上,根据赋权能力将无线传感网络节点分为高级节点和普通节点,并利用混合密钥分配技术,分别提升两类节点的安全性能。通过将节点映射至粒子传感器的工作区域内,实现无线传感网络安全分簇。测试结果表明,所提方法“死亡节点”留存时间低于0.2 s,数据包传输总量高于900 bit。

基于平衡生成对抗网络的海洋气象传感网入侵检测研究

针对海洋气象传感网(MMSN)环境下海洋移动终端资源受限和网络流量不平衡导致网络入侵难以被准确检测的问题,提出了一种基于移动边缘计算的MMSN物理架构和一种基于平衡生成对抗网络的入侵检测模型。首先,利用改进的平衡生成对抗网络对不平衡数据进行数据增强。其次,利用基于分组卷积的轻量级网络对入侵数据进行分类。最后,通过计算机仿真证明了所提模型较传统数据增强模型具有更高识别各类攻击的能力,尤其是针对MMSN的少数类样本攻击。

Distributed Aggregation Algorithms for Mobile Sensor Networks with Group Mobility Model

In many applications of mobile sensor networks, such as water flow monitoring and disaster rescue, the nodes in the network can move together or separate temporarily. The dynamic network topology makes traditional spanning-tree-based aggregation algorithms invalid in mobile sensor networks. In this paper, we first present a distributed clustering algorithm which divides mobile sensor nodes into several groups, and then propose two distributed aggregation algorithms, Distance-AGG （Aggregation based on Distance）, and Probability-AGG （Aggregation based on Probability）. Both of these two algorithms conduct an aggregation query in three phases： query dissemination, intra-group aggregation, and inter-group aggregation. These two algorithms are efficient especially in mobile networks. We evaluate the performance of the proposed algorithms in terms of aggregation accuracy, energy efficiency, and query delay through ns-2 simulations. The results show that Distance-AGG and Probability-AGG can obtain higher accuracy with lower transmission and query delay than the existing aggregation algorithms.

传感器网络中一种基于分布式更新权限的组密钥管理方案

传统网络中的组密钥管理方案一般依赖于一个长期可信的节点,由该节点存储其他所有用户的信息进行组密钥管理.与传统网络不同的是传感器网络不存在这种可信节点,而且其资源十分有限,因此传统网络中的组密钥管理方案不适合传感器网络.结合传感器网络的特性,提出一种基于分布式更新权限的组密钥管理方案DRA,DRA在组密钥更新过程中引入广播机制,并构造权限分布函数、组密钥隐藏函数及广播认证函数以实现对妥协节点的剔除(revocation)及更新信息的完整性鉴别.理论分析及仿真结果表明,方案DRA在保证安全性的同时具有较小的存储开销和通信开销,并能有效地避免孤立节点的问题.

延迟容忍传感器网络中基于群组运动的事件传输

提出了一种基于分布式群组移动的事件分类传输策略GMED(distributed group mobility adaptive event delivery).通过有效地发现和利用传感器节点在运动过程中形成的群组,建立基于群组的事件分类传输模型,改善数据传输性能.其中,群组的转发是依据各自与汇聚点的机会概率按照多副本方式进行的;而群内的事件传输则是基于各成员的稳定邻居集建立传输路径,并以单副本方式进行.队列管理则根据事件的优先级决定递交的顺序和丢弃原则.此外,引入冗余副本控制机制,优化副本管理,降低网络负载.模拟实验结果表明,与现有的几种DTMSN(delay tolerant mobile sensor networks)数据传输算法相比,GMED能以较低的数据传输能耗和传输延迟获得较高的数据传输成功率,且网络寿命相对较长.

一种无线传感器网络的密钥管理方案

为了在有限资源的无线传感器网络能安全进行群组通信,使用对称加密算法和单向哈希函数提出了一种具有有效性和扩充性的组密钥管理方案,并可满足前向和后向安全性。与目前现有的群组密钥相比,方案不仅具有较好的效率,并且更适合于无线传感器网络。

无线传感器网络中基于簇协作的分布式组密钥管理方案

处于敌对环境的传感器网络极易遭到攻击,且不存在长期可信的节点可以担当组管。提出一种分布式组密钥管理方案,方案基于簇形结构,充分利用簇内通信及簇间通信的局部特性,对组密钥协作更新。当妥协节点总数在门限以内的某簇检测出节点妥协时,该簇的簇头发起更新,并通过簇内协作将该节点撤销;当某簇妥协节点数目在门限以上时,由该簇邻居簇的簇头发起更新,并通过簇间通信将该簇妥协节点撤销。与已有方案相比较,此方案能实时地更新组密钥,有着更好的安全性并具有较小的通信开销。

传感器网络中基于随机混淆的组密钥管理机制

组密钥在传感器网络安全组通信及虚假数据过滤等安全服务中起着重要作用.针对节点可能被大量俘获这一安全威胁研究组密钥管理问题,提出了一种基于随机混淆技术的组密钥管理机制GKRP(group key management scheme based on random perturbation).首先,提出了一种基站与网络协同的组密钥管理框架;然后,结合秘密共享技术和随机混淆技术构造了组密钥广播函数和局部协作等功能函数,以实现组密钥更新信息的广播传输和多个被俘获节点的撤销;最后,基于上述管理框架和函数,提出了机制GKRP,使得节点间可以协作进行组密钥更新.理论分析及仿真结果表明,GKRP在特定的参数设置下不受限于被俘获节点,且该参数易于满足.因此,GKRP有效突破了门限值问题,提高了网络的抗毁性.同时,由于采取局部广播和全网络广播方式更新组密钥,GKRP在通信上同样更为有效.GKRP的存储和计算开销略高于已有同类机制,但仍然较低,适合于传感器网络.

移动无线传感器网络群组移动的连通性保证

鉴于移动无线传感器网络的节点在群组移动过程中会破坏网络整体连通性的情况,基于节点本身的移动特性,分别提出了构建连通路径以及记号路径的解决方案。通过优化路径节点数,均衡路径节点的能耗以及判定各节点的移动指数,最终依靠节点的级联移动或者有序脱离完成相应链路的构建。仿真分析表明,方案能够有效地保证群组移动后网络的连通性。

无线传感器网络中的传感器节点分组控制策略

研究无线传感器网络(WSNs)的传感器节点分组控制策略和软件实现方法。针对WSNs通信问题和分布监测的实际需求,制定传感器节点分组控制策略、单元组的模块化控制流程以及故障处理方法,保证多节点监测独立性、相关节点采集同步性以及数据传输可靠性。在程序实现方面,建立通信接口层、消息分发层、策略控制层组成的软件架构,实现WSNs远程控制软件,并进行了多传感器节点控制和数据传输可靠性的测试实验。

面向目标跟踪的传感器网络分布式组管理机制

移动目标跟踪是无线传感器网络中的重要研究课题和研究热点之一。分布式组管理机制是移动目标跟踪系统的核心组件,是系统达到高可扩展性和低能耗的关键。本文提出了一种基于目标射频信号强度的贪婪式组管理机制,从组的构建和组的维护2个方面对其工作机理进行了详细阐述,并针对系统运行时可能出现的各种异常状况给出相应的解决方案。本文最后给出了组管理机制在TinyOS平台上的具体实现,以及在实际中的部署效果和从中获得的经验。

基于群密钥协商的无线传感器网络签名协议

为确保信息在无线传感器网络安全传输,提出了一个新的基于群密钥的安全协议。通过离散对数和哈希链的使用,可确保信息不被攻击者伪造或窃取。同时,考虑到无线传感器网络是由大量能量有限的节点构成,其计算能力不高,生存周期较短的特性,为节省传感器电池能量,降低能源的消耗,在初始化阶段传感器节点发送数据前通过服务器来完成群密钥协商。经过实验和理论分析,所提出协议的安全和效率整体上优于其他协议。

一种无线传感器网络的组密钥管理方案研究

为了在有限资源的无线传感器网络上能安全进行群组通讯,同时考虑到组密钥管理必须满足前向安全性、后向安全性和完整性的安全需求,使用椭圆曲线密码体制的部分步骤和异或运算提出了一种安全有效的组密钥管理方案。与目前现有的群组密钥相比,方案不仅具有较好的效率,并且更适合于无线传感器网络。

基于链路层重传的传感器网络可靠传输模型

无线传感器网络的通信链路是极其不可靠的。提出了路径效率这一新的链路质量度量参数,以路径效率为主要指标分析了传统的数据链路层可靠传输模型,并提出了一种以效率为中心的组确认模型,该模型通过减少反向链路数据重传请求包的个数,有效地降低数据传输中的冗余信息,极大地提高网络的路径效率,从而节约能耗。通过NS-2仿真工具对组确认模型的性能进行了测试,结果表明该模型更适合于资源受限的传感器网络的应用。

分组敏感的无线传感器网络实时数据融合树算法

针对无线传感器网络中数据传输必须在指定时延约束下完成的特殊场景提出了一种能量有效的数据融合树算法,该算法首次将分组敏感的概念引入到传感器网络实时数据融合应用中,并通过特殊机制使得该算法在降低能耗水平的同时可以为实时数据动态地选择满足时延要求的路径。另外,针对该数据融合树算法设计了一种特殊的数据融合定时机制,从而进一步改善了该算法的性能。最后,通过仿真试验将该算法与已存在算法进行了比较,证明了该算法的优越性。