Secure communication in CloudIoT through design of a lightweight authentication and session key agreement scheme

Internet of Things (IoT) is a newly emerged paradigm where multiple embedded devices, known as things, are connected via the Internet to collect, share, and analyze data from the environment. In order to overcome the limited storage and processing capacity constraint of IoT devices, it is now possible to integrate them with cloud servers as large resource pools. Such integration, though bringing applicability of IoT in many domains, raises concerns regarding the authentication of these devices while establishing secure communications to cloud servers. Recently, Kumari et al proposed an authentication scheme based on elliptic curve cryptography (ECC) for IoT and cloud servers and claimed that it satisfies all security requirements and is secure against various attacks. In this paper, we first prove that the scheme of Kumari et al is susceptible to various attacks, including the replay attack and stolen-verifier attack. We then propose a lightweight authentication protocol for secure communication of IoT embedded devices and cloud servers. The proposed scheme is proved to provide essential security requirements such as mutual authentication, device anonymity, and perfect forward secrecy and is robust against security attacks. We also formally verify the security of the proposed protocol using BAN logic and also the Scyther tool. We also evaluate the computation and communication costs of the proposed scheme and demonstrate that the proposed scheme incurs minimum computation and communication overhead, compared to related schemes, making it suitable for IoT environments with low processing and storage capacity.     

一种3D眼镜虚拟试戴系统的实现

针对人脸图像试戴3D眼镜过程中存在的镜腿遮挡人脸问题,文中提出一种基于人脸图像的3D眼镜虚拟试戴技术。利用构建的人脸形状的三维模型,使其在虚拟试戴中对镜腿起到消隐作用,解决镜腿的遮挡问题。文中对输入的人脸图像进行关键点检测,结合Graham扫描法求得人脸形状的凸多边形,利用平移扫描构建人脸形状的三维模型。此外,文中根据定位人脸图像上的关键点以及姿态估计后对三维眼镜模型的变换,将眼镜模型佩戴到人脸图像上。实验结果表明,该方法对于多视角的人脸图像实现了虚拟试戴效果,解决了多种视角下人脸图像试戴过程中镜腿的遮挡问题,虚拟试戴中镜腿遮挡平均准确率为94.5%,遮挡精度较高。     

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

IGBT芯片静态输出曲线连续测量方法

绝缘栅双极型晶体管(IGBT)芯片的静态输出曲线是考核其能量损耗及指导多芯片并联设计的重要指标之一。现有测量IGBT静态输出曲线的方法多采用商用化的功率器件分析仪,然而商业化功率器件分析仪存在价格昂贵、夹具单一的问题。亟需开发一种简单、快速、有效的静态输出曲线测量方法。面向高压IGBT芯片,提出一种新的静态输出曲线连续测量方法及测试电路,有效减小了IGBT芯片的电导调制效应和温升效应对静态输出曲线的影响。通过实时测量动态过程中的电压及电流,可以快速得到IGBT芯片静态输出曲线。通过对比本文连续法与功率器件分析仪的测量结果,证明了所提方法的有效性。     

组合跳变随机平移宽间隔混沌跳频序列设计

为进一步提高宽间隔跳频序列的性能,基于混沌跳频序列,针对随机平移替代法存在的“窄点”平移与序列平衡性的矛盾问题,提出了一种新的组合跳变随机平移法。该方法在随机平移替代法的基础上取消“窄点”修正,引入组合跳变序列控制频点宽间隔映射。为兼顾组合跳变随机平移法产生序列的平衡性、汉明自相关性和宽间隔特性,构造了跳频序列的复合目标优化函数,引入粒子群算法计算得到最优的序列控制参数。仿真结果表明,组合跳变随机平移法可构造更多的序列,且产生的宽间隔混沌跳频序列具有更好的平衡性、汉明相关性和复杂度,采用粒子群优化获取的控制参数可以实现序列性能的均衡最优。     

一种波形可移植性量化评估的模糊综合评判法

要实现高效低成本的波形跨平台移植,需要通过量化评估优选出可移植性强的波形来进行移植。针对波形可移植性量化评估重要性,分析了影响波形可移植性量化评估的重要因素,提出了一种有效的波形可移植性量化评估模糊综合评判法,以软件无线电硬件平台因素为例论述了该方法的实现原理及流程。通过验证表明,该方法合理可行,具有很好的应用价值。     

黑磷纳米盘-层等离激元系统中的各向异性可调多阶强耦合

黑磷支持各向异性的表面等离激元,可用于设计具备更多功能的原理性器件。用时域有限差分法数值模拟了中红外到远红外波段基于黑磷的层-盘-层系统中不同等离激元模式之间的杂交行为。通过动态调节黑磷中的载流子浓度,可以实现两个晶格方向上强耦合现象的产生与控制。对不同模式间的耦合进行分析并计算,得到吸收光谱中的拉比分裂能最高可达42.9 meV。此外,还计算了偏振角度对各向异性强耦合的影响,其最高可以实现6个吸收频带。该模型可为构建未来在中远红外波段工作的基于二维材料紧凑型各向异性等离激元器件提供基础。     

偏振三维成像仪的相对偏振方向定标方法

在介绍偏振三维成像机理、四孔径偏振三维成像仪组成的基础上,开展四孔径相对偏振方向对偏振三维成像精度影响分析,确定四孔径相对偏振方向精度要求。制定了四孔径镜头偏振片相对偏振方向定标方法和四孔径偏振三维成像仪相对偏振方向定标方法,搭建了定标装置,在实验室内开展了相对偏振方向定标。四孔径镜头偏振片相对偏振方向定标误差为±0.5o,四孔径偏振三维成像仪相对偏振方向误差为±1o,从而可保证偏振三维反演的法向量误差为-5.47%~5.80%,为偏振三维成像仪高质量成像提供保障。     

面向植被边坡的地基SAR高相干点选择

基于高相干点进行相位分析,才能有效保证地基SAR（Synthetic Aperture Radar,合成孔径雷达）形变测量的准确性。在差分干涉测量领域中,广泛使用幅度离差法,可以有效地选择出岩石、建筑物等PS（Permanent Scatterer,永久散射体）点作为高相干点,但对于植被边坡,采用该方法选择出高相干点数量较少,不利于差分干涉处理。在星载SAR领域,普遍采用StaMPS方法解决植被边坡的高相干点选择问题。本文探索了StaMPS方法在地基SAR领域的适用性,提出采用非PS点来计算相干系数门限,并引入DS（Distributed Scatterer,分布式散射体）选择技术,进一步提高了高相干点的数量。对一处植被边坡的实验结果表明,相比于幅度离差法和StaMPS方法,改进方法在提高高相干点数量的同时,有效保证了其相位质量。      

基于测量误差不确定性加权的快速相机位姿估计算法

在相机位姿估计任务中,参考点位置的测量容易受测量仪器或者所处环境影响,出现一定程度的测量误差,其中误差较大的点对最终求解精度的影响很大,被称为野值点。文章针对现有算法抗野值点能力较弱的问题,提出一种基于测量误差不确定性加权的快速相机位姿估计算法。该算法以经典的正交迭代算法为基础,引入M估计方法,对目标函数根据参考点的测量误差赋予相应大小的权值,最大程度地将野值点的影响排除,并引入Kronecker积对计算过程进行优化,减少了迭代过程中的冗余计算,提高运算速度。仿真实验结果表明,改进后的算法提升了原算法的抗野值点能力,且计算速度更快。