Heterogeneous Fault-Tolerant Aggregate Signcryption with Equality Test for Vehicular Sensor Networks

The vehicular sensor network (VSN) is an important part of intelligent transportation, which is used for real-timedetection and operation control of vehicles and real-time transmission of data and information. In the environmentofVSN, massive private data generated by vehicles are transmitted in open channels and used by other vehicle users,so it is crucial to maintain high transmission efficiency and high confidentiality of data. To deal with this problem, inthis paper, we propose a heterogeneous fault-tolerant aggregate signcryption scheme with an equality test (HFTASET).The scheme combines fault-tolerant and aggregate signcryption,whichnot onlymakes up for the deficiency oflow security of aggregate signature, but alsomakes up for the deficiency that aggregate signcryption cannot tolerateinvalid signature. The scheme supports one verification pass when all signcryptions are valid, and it supportsunbounded aggregation when the total number of signcryptions grows dynamically. In addition, this schemesupports heterogeneous equality test, and realizes the access control of private data in different cryptographicenvironments, so as to achieve flexibility in the application of our scheme and realize the function of quick searchof plaintext or ciphertext. Then, the security of HFTAS-ET is demonstrated by strict theoretical analysis. Finally, weconduct strict and standardized experimental operation and performance evaluation, which shows that the schemehas better performance.

A Novel Routing Algorithm for Vehicular Sensor Networks

Recent advances in wireless communications are diffusing into many new applications. The tiny sensor node, which consists of sensing, data processing and communicating components, led to the idea of sensor networks. A sensor network composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The applications envisioned for sensor networks vary from monitoring inhospitable habitats and disaster areas to operating indoors for intrusion detection and equipment monitoring. In most cases the network designer would have little control over the exact deployment of the network. Nowadays Vehicular Networks are drawing lots of attention due to the wide variety of applications that they can provide. These applications include traffic monitoring, positioning, security etc. A lot of research work is being conducted to define the standard for vehicular communication. These include frequency allocation, standards for physical and link layers, routing algorithms, security issues and new applications. In this paper we discuss the disadvantages of the traffic monitoring by traditional methods and by using GPS equipped sensors. Then we propose a new routing protocol for a fixed topology containing both stationary and mobile nodes. We also try to optimize the energy of the sensor nodes. We simulate our routing algorithm in MATLAB and evaluate it for different possible cases.

车载社交网中基于密文属性加密的车队车辆数据共享方案

针对车载社交网(VSN)中车队车辆数据共享过程中存在的隐私泄露问题,提出一种基于密文属性的加密方案。利用基于属性的加密技术,保证仅授权的车辆可访问数据,防止车队车辆数据共享过程中发生隐私泄露;针对车队车辆数据共享时生成访问策略时间开销大、数据共享效率低的问题,通过构造访问树实现对访问策略的设计,利用路侧单元将访问树转化为访问矩阵,实现访问策略的快速生成。仿真分析结果表明,该方案能够实现对VSN中车队车辆的数据安全共享,所构建的访问策略生成方案能够有效降低车辆的计算开销。

SAFT-VNDN: A Socially-Aware Forwarding Technique in Vehicular Named Data Detworking

Vehicular Social Networks(VSNs)is the bridge of social networks and Vehicular Ad-Hoc Networks(VANETs).VSNs are promising as they allow the exchange of various types of contents in large-scale through Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication protocols.Vehicular Named Data Networking(VNDN)is an auspicious communication paradigm for the challenging VSN environment since it can optimize content dissemination by decoupling contents from their physical locations.However,content dissemination and caching represent crucial challenges in VSNs due to short link lifetime and intermittent connectivity caused by vehicles’high mobility.Our aim with this paper is to improve content delivery and cache hit ratio,as well as decrease the transmission delay between end-users.In this regard,we propose a novel hybrid VNDN-VSN forwarding technique based on social communities,which allows requester vehicles to easily find the most suitable forwarder or producer among the community members in their neighborhood area.Furthermore,we introduce an effective caching mechanism by dividing the content store into two parts,one for community private contents and the second one for public contents.Simulation results show that our proposed forwarding technique can achieve a favorable performance compared with traditional VNDN,in terms of data delivery ratio,average data delivery delay,and cache hit ratio.

A Novel Range-Free Jammer Localization Solution in Wireless Network by Using PSO Algorithm

In wireless networks, jamming attacks are easy to launch and can significantly impact the network performance. The technique which localizes the jamming attacker is useful to address this problem. Some range-based localization schemes depend on the additional hardware of wireless nodes too much, and they can not work in resource-constrained wireless networks. Solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches.In this paper, we propose a novel range-free algorithm to localize the source of the attacker. We show that our approach only relies on the positions of each jammed or no-jammed node in the network, PSO algorithm is used to get the minimum covering circle of jammed positions and the circle center is the estimated jammer location. We compare our work with some existing range-free solutions via extensive simulations in two models, which are wireless sensor network (WSN) and vehicular ad hoc network (VANET) respectively. The experimental results suggest that our proposed algorithm achieves higher accuracy than the other solutions, and the localization error goes down with larger number of recorded jammed positions. In additional, when the recorded jammed positions are distributed in a specific constrained area, the localization error goes higher, we also propose an improved PSO algorithm to deal with this issue.

基于博弈分析的车辆感知网络节点轨迹隐私保护机制

利用车辆移动"众包模式"为驾驶员提供实时路况信息和探索新的商业服务模式,是车载感知网络的新型应用之一.然而,车辆移动轨迹中的敏感信息易与用户身份相关联,存在隐私泄露问题.提出了一种车载感知网络节点轨迹隐私保护算法,克服了匿名和隐藏技术缺乏数据真实性权衡的缺点,并考虑到多种攻击策略的影响.对于给定的一系列轨迹集,首先确定边信息概率分布,建立攻击者和防御者模型,通过求解攻防博弈中的纳什均衡选择最优的防御策略,并证明其有效性.在此基础上,折中轨迹数据真实性和隐私性,以最大化防御者效用为目标,提出轨迹隐私保护算法.实验结果表明,防御策略在不同的攻击策略下展现出不同的性能,算法所选择的防御策略优于其他的策略.

基于定向扩散的车辆传感器网络连通性研究

为改善车辆传感器网络的实时连通性问题,提出一种路边节点梯度值可滑动的定向扩散梯度场DDGF-SRG,并给出了梯度场的实时动态调整规则。通过给路边节点分配固定梯度值,将规模巨大车辆传感器网络划分成若干以路边节点为核心的局部区域,以使梯度场的建立和动态更新可在各局部区域内分布式进行,提高梯度场建立和更新的实时性。通过给车辆节点分配一个可变的数据汇聚梯度值,建立车辆节点到路边节点的定向扩散梯度;通过给路边节点分配一个可变的数据汇聚梯度值,建立路边节点到低梯度层次的定向扩散梯度,并将各局部区域梯度场链接成一个全局的定向扩散梯度场。理论分析和仿真结果表明,DDGF-SRG梯度场在进行动态调整和利用车辆传感器网络的延迟容忍运载能力后,车辆传感器网络的实时连通性得到了极大改善。

基于双重梯度的车辆传感器网络定向扩散梯度场

为了提高定向扩散梯度场建立的快速性和逻辑网络的实时连通性,提出一种基于双重梯度的车辆传感器网络(VSN)定向扩散梯度场(DDGF-DG)。通过网络中各路边节点估算的梯度值将网络划分为若干以路边节点为局部核心的区域,各局部核心分布式启动局部定向扩散梯度场的建立,利用双重梯度值将各局部定向扩散梯度场连接成全局定向扩散梯度场,实现巨大规模车辆传感器网络的分区治理。理论分析和仿真结果表明,基于双重梯度的定向扩散梯度场及其动态调整有利于减小梯度场建立与维护的时间开销和提高网络的实时连通性。

车辆传感器网络研究

随着无线通信技术的快速发展和车辆在日常生活中的不断普及,车辆传感器网络作为新一代的网络技术越来越被重视。文章基于无线车辆传感器网络的基本概念和体系结构,讨论了车辆传感器网络与传统无线传感器网络的主要区别,以及由此引入的各种设计上的挑战。对车辆传感器网络中的关键技术,包括媒体访问控制(MAC)协议、路由协议和移动模型,文章进行了研讨,并介绍了世界上已建立的车辆传感器网络试验床。文章还介绍了行车安全、城市监控、路况监测、交通流量监测等几种典型的车辆传感器网络的应用。

基于半马尔科夫决策过程的虚拟传感网络资源分配策略

针对传统无线传感网络(WSN)中资源部署与特定任务的耦合关系密切,造成较低的资源利用率,进而给资源提供者带来较低的收益问题,根据虚拟传感网络请求(VSNR)的动态变化情况,该文提出虚拟传感网络(VSN)中基于半马尔科夫决策过程(SMDP)的资源分配策略。定义VSN的状态集、行为集、状态转移概率,考虑传感网能量受限以及完成VSNR的时间,给出奖赏函数的表达式,并使用免模型强化学习算法求解特定状态下的行为,从而最大化网络资源提供者的长期收益。数值结果表明,该文的资源分配策略能有效提高传感网资源提供者的收益。

泛在互联车辆传感器网络混合拓扑结构研究

针对泛在互联车辆传感器网络的特点,提出了一种基于位置和定向扩散机制的泛在互联车辆传感器网络混合逻辑拓扑结构HLT-L&DD(hybrid logical topology based on location and directed diffusion mechanism),并给出了形成HLT-L&DD的控制方法。在HLT-L&DD中,各路边节点根据任务需求自定为簇首,以其位置信息作为其所在分簇的簇标识ID,并以定向扩散机制分布式启动分簇过程,逐跳吸纳跳数距离近的车辆节点加入本簇,不同的路边节点独立形成若干个分簇;各相邻分簇之间通过边沿节点的定向扩散机制实现彼此相联,最终将各独立分簇互联成一个完整的混合逻辑拓扑结构HLT-L&DD。HLT-L&DD是平面逻辑拓扑结构与层次型逻辑拓扑结构的混合拓扑结构,既便于车辆传感器网络节点的泛在自组成网、分区自治,也便于路边节点与其他诸如Internet等传统网络的泛在互联。理论分析和仿真结果表明,HLT-L&DD有利于减小泛在互联车辆传感器网络逻辑拓扑结构建立与动态维护的时间开销,以及提高网络的实时连通性,从而优化泛在互联车辆传感器网络的综合性能。

视觉传感网中基于二次规划的图像压缩感知

为降低视觉传感网络中图像压缩感知算法的计算复杂度,提出一种基于二次规划的网络图像恢复算法。该算法将压缩感知重构中的欠定线性方程组求解问题,转化为有界约束二次规划问题,在此基础上结合阿米霍步长准则,设计一种压缩感知图像恢复算法,通过求解二次规划问题对网络图像数据进行恢复。理论分析和仿真结果表明,与传统图像压缩感知算法相比,该算法可减少约1/3的图像数据恢复运算时间,且图像重构质量提高3 dB^6 dB,有效提高了视觉传感器网络图像恢复算法的实时性。

车载传感网中基于群特性的MaxProp路由协议改进

车载传感网中信息传输面临的主要难题是网络间歇性连通和拓扑高度动态变化,以往常常采用机会转发的思想设计路由协议来解决此难题。但现有的机会路由协议忽略了网络中部分车辆节点具有群组移动的特点,从而导致协议在群组移动场景下的性能急剧下降。为此,通过对最大相遇概率路由进行改进,提出了一种基于群特性的MaxProp路由协议。该协议利用群组内成员节点之间极好的连通性,通过群内消息扩散,间接提高群内节点与群外节点之间的相遇概率,从而增加了消息转发机会。并在ONE仿真平台上,与其他几种经典的机会路由协议相对比,改进后的MaxProp路由协议在消息传输成功率、网络开销比方面具有明显提升。

基于统计假设检验的虚拟传感网容错策略

为了减少多应用目标的传感器网络的能量消耗和实现较高的故障传感器节点识别率,在基于簇树的虚拟传感器网络框架上,通过检验本地数据采集序列与事件统计特征的符合程度来判断错误是否发生,充分利用了随机过程描述事件的时间相关性,提出了一种基于统计假设检验的虚拟传感器网络容错策略.实验结果表明,在任意节点能量耗尽之前,多事件监测比单事件监测产生更少的单播消息量,却分发更多的多播消息.而且,随着传感器节点错误概率的增加,系统能保持较理想的节点错误识别率和事件区域监测概率.

基于无线传感器网络的车辆跟踪算法设计与分析

设计了一种基于传感器网络的车辆跟踪方法,为了达到降低能量消耗的目的,文中结合车辆动力学的知识,减小跟踪区域,减少活动节点个数.现实中,车辆运动带有目的性,车辆的位置和速度在时间上具有相关性,为此本论文采用GM模型来预测车辆下一时刻的位置,依据车辆位置来更新跟踪区域,确保移动目标始终处于跟踪区域内.仿真结果表明,相对于OCR法,本方法降低了22%的能量开支.

基于能量分级和位置预测的高效路由算法

针对车载传感器网络节点移动速度快、网络拓扑结构不稳定、终端传感器节点能量不确定性等特点,提出了一种能量分级和位置预测的高效路由算法ERLP(Energy Rank and Location Prediction based routing)。该算法根据具有不同能量等级的节点将消息传递距离的不同选择那些能量高的节点作为中转节点,并结合节点的分布区域和当前速度,尽量将多个消息副本传递给覆盖不同方向的节点,避免消息传递的局部性。仿真结果表明,与当前典型延迟容忍网络的路由算法相比,ERLP算法在传输成功率、平均延迟时间上具有较大提升。

车载传感网中基于聚合签名的认证方案

利用无证书公钥密码体制构造一种新的聚合签名算法,以实现车载传感网中车辆节点之间信息传输的安全认证.该方案通过路侧单元生成的影子值与周围节点进行通信,实现了车辆用户的条件隐私保护.实验结果表明,该方案不仅能消除复杂的证书维护成本,也解决了密钥托管问题,且满足了消息的认证性、匿名性、不可伪造性和可追踪性等性质,通信效率较高,消息验证时延较短.

A Survey of VASNET Framework to Provide Infrastructure-Less Green IoTs Communications for Data Dissemination in Search and Rescue Operations

implementation of wireless technologies based on the vehicular ad hoc sensor network （VASNET） may provide support for the search and rescue （SAR） team to operate effectively in natural disaster events, such as landslide, earthquake, flooding, and tsunami. The operations of SAR team are very challenging in such events due to the possible damages of the existing telecommunication infrastructures. The existing deployment of the cellular communications infrastructure may be partially or completely destroyed after the occurrence of these natural disasters. Thus, the current VASNET infrastructure must be able to support the infrastructure-less network by integrating other green wireless technologies that can benefit the SAR team, which can indirectly save more human lives and reduce the number of casualties. Therefore, the integration of green Internet of things （loT） and VASNET is proposed to form a heterogeneous framework for data dissemination in SAR operations. In addition, this paper also discusses the existing lot framework in disaster scenarios with future research direction for IoT using on any aspect, especially related to the natural disaster scenarios.

Accurate Distance Estimation for VANET Using Nanointegrated Devices

Vehicular Ad-Hoc Networks (VANET) is a research venue that promises for many useful applications. Most of these applications require a precise real-time positioning system for each vehicle. However, practically the existing tecniques are still not accurate and hence not suitable for some critical applications. In this paper, we will focus on the most critical ones which are the collision avoidance, and collision warning, or lane-tracking. Collision occurs when the distance between nearby vehicles decreases rapidly. Hence, an accurate and precise knowledge of the distance among each vehicle and all the surrounding vehicles has to be obtained to enable a realistic collision avoidance service. We propose to use the carbon nanotube network (CNT) integrated with other nano-devices that can provide accuracy in the order of millimeters. In this paper, theoretical investigations and mathematical formulations are presented. The obtained results show the effectiveness and accuracy of the proposed methodology.

基于车辆传感网的交通路网自动提取方法研究

为适应交通路网规划和智能驾驶等应用的需要,基于泛在互联车辆传感网对交通路网及其边界进行自动提取。车辆传感网中的运动车辆对其自身位置进行实时感知,并将感知数据经泛在互联网络汇聚至应用服务器,应用服务器根据同一时刻的运动车辆的位置信息构建一幅幅实时分布场景,并将适当时间间隔的多幅实时分布场景迭加成一幅增强分布场景,并在增强分布场景中沿不同的方向搜寻路网边界运动车辆节点,最后根据搜寻结果综合标定出交通路网边界节点,并据边界节点提取出交通路网边界。实例分析表明,该方法提取的交通路网及其边界基本准确,可为交通路网规划和智能驾驶等应用提供支撑。