IP2DM: integrated privacy‐preserving data management architecture for smart grid V2G networks

With the development of battery vehicles, vehicle‐to‐grid (V2G) networks are becoming more and more important in smart grid. Although battery vehicles are environmentally friendly and flexible to use two‐way communication and two‐way electricity flow, they also raise privacy‐preservation challenges, such as location and movement privacy. On the one hand, utility companies have to monitor the grid and analyze user data to control the power production, distribution, scheduling, and billing process, while typical users need to access their data later online. On the other hand, users are not willing to provide their personal data because they do not trust the system security of the utility companies where their data stored, and it may potentially expose their privacy. Therefore, in this paper, we study data management of V2G networks in smart grid with privacy‐preservation to benefit both the customers and the utility companies. Both data aggregation and data publication of V2G networks are protected in the proposed architecture. To check its security, we analyze this architecture in several typical V2G networks attacks. We conduct several experiments to show that the proposed architecture is effective and efficient, and it can enhance user privacy protection while providing enough information for utility companies to analyze and monitor the grid. Copyright © 2016 John Wiley & Sons, Ltd.     

基于对数域同态滤波的时延估计算法研究

针对水声信道中窄带信号的多途时延估计问题,本文在对复倒谱时延估计方法进行研究的基础上,提出了一种基于对数域同态滤波的时延估计算法.结合复倒谱与同态滤波思想,将接收的窄带信号首先变换到对数域,然后与本地存储的信号进行谱减法,再对相减后的信号进行滤波以消除残余的信号与噪声成分,最后将其恢复到时域以获取多途时延估计.与传统的匹配滤波/相关处理以及复倒谱分析方法相比,本文算法具有时延估计精度高、噪声抑制能力较强等特点.仿真与湖试数据处理结果证明了该方法的有效性.     

隐私保护DNA序列汉明距离计算问题

DNA序列承载着人体重要的生物学信息，如何在保护隐私的情况下正确地对不同的DNA序列进行比对，成为亟待研究的科学问题。汉明距离在一定程度上刻画了两个DNA序列的相似程度，在保护隐私的情况下，研究DNA序列的汉明距离计算问题。首先定义了DNA序列的0-1编码规则，该规则将长度为n的DNA序列编码成长度为4n的0-1串，证明了两个DNA序列的汉明距离等于它们的0-1编码串的汉明距离的一半。以此结论为基础，以GM加密算法为主要密码学工具，构造了计算DNA序列汉明距离的一个安全两方计算协议。在半诚实攻击者模型下，证明了协议的正确性，给出了基于模拟器的安全性证明，并对协议的效率进行了分析。     

一种小波变换的小波系数均衡图像增强算法

介绍了几种经典的图像增强算法,依据经典直方图均衡化算法思想,提出了在小波变换下的小波系数均衡化图像增强算法,并给出了计算步骤。与经典直方图均衡化算法、同态滤波实验结果相比较,表明提出的算法可有效增强图像、抑制噪声。     

同态滤波的一种GPU提速实现方法

为了提高光照不均图像的增强速率,提出了基于GPU平台的同态滤波并行算法.根据同态滤波算法的并行性,利用CUDA软硬件体系架构,实现了同态滤波算法向GPU上的移植.利用多幅不同分辨率图像作为测试数据,对比CPU和GPU方案的计算效率.实验结果表明,GPU实现方案大幅度提升了计算效率.     

基于EMD与同态滤波解调的矿用齿轮箱故障诊断

针对矿用齿轮箱振动信号的特点,提出了一种基于经验模态分解(empirical mode decomposition,简称EMD)与同态滤波相结合的故障解调方法.利用EMD对某矿用皮带机齿轮箱故障信号进行分解,得到若干个本征模态函数(intrinsic mode functions,简称IMFs)分量,然后对其中较突出的IMFs进行同态滤波解调分析,提取出了频率为7.0Hz的调制故障信号.研究表明,EMD与同态滤波解调相结合是一种有效的齿轮箱故障诊断方法.     

Attribute Based DRM Scheme with Dynamic Usage Control in Cloud Computing

In order to achieve fine-grained access control in cloud computing, existing digital rights management （DRM） schemes adopt attribute-based encryption as the main encryption primitive. However, these schemes suffer from inefficiency and cannot support dynamic updating of usage rights stored in the cloud. In this paper, we propose a novel DRM scheme with secure key management and dynamic usage control in cloud computing. We present a secure key management mechanism based on attribute-based encryption and proxy re-encryption. Only the users whose attributes satisfy the access policy of the encrypted content and who have effective usage rights can be able to recover the content encryption key and further decrypt the content. The attribute based mechanism allows the content provider to selectively provide fine-grained access control of contents among a set of users, and also enables the license server to implement immediate attribute and user revocation. Moreover, our scheme supports privacy-preserving dynamic usage control based on additive homomorphic encryption, which allows the license server in the cloud to update the users＇ usage rights dynamically without disclosing the plaintext. Extensive analytical results indicate that our proposed scheme is secure and efficient.     

基于 RLWE 的全同态加密方案简

基于Kristin Lauter等人的somewhat同态方案,提出“带密钥转换的重线性化技术”。结合该技术与“模转换”,设计了一个基于RLWE的非自举的层次化全同态加密方案。该方案的同态操作简单,而且给出的平凡门操作使得电路层结构更清晰。最后利用自举技术作为优化提升了方案的同态运算能力。     

利用容错学习问题构造基于身份的全同态加密体制简

基于容错学习问题构造的一类全同态加密体制在云计算安全领域具有重要的潜在应用价值,但同时普遍存在着公钥尺寸较大的缺陷,严重影响其身份认证与密钥管理的效率。将基于身份加密的思想与基于容错学习问题的全同态加密相结合,提出一种基于身份的全同态加密体制,能够有效克服公钥尺寸对于全同态加密应用效率的影响。在随机喻示模型下,体制的安全性归约到容错学习问题难解性和陷门单向函数单向性,并包含严格的安全性证明。     

基于小波域热红外降质图像滤波增强方法研究

随着现代网络传输和视频通信技术的快速发展,大大拓宽了热红外图像的应用领域。提出了一种基于小波变换的热红外将质图像滤波增强方法。该方法以受到不同强度高斯白噪声和脉冲噪声构成的混合噪声模型的热红外降质图像为研究对象,首先对其进行二维小波变换,从而获得高频和低频小波分解系数;鉴于低频小波分解系数包含图像大部分信息,基本不受噪声干扰的特点,引入直方图均衡化法进行增强处理,以改善图像低频信息的对比度;根据各方向的小波高频分解系数中噪声的分布特征,对经典数学形态学滤波算法进行研究,分别设计出几类多尺度多方向的结构元素,实现对各高频小波分解系数中噪声的三级串联滤波处理,在此基础上进行自适应同态滤波增强,以最大限度改善滤波后图像质量。最后进行小波分解系数重构。实验结果表明,该算法对于热红外将质图像的处理效果优于单纯进行经典数学形态学滤波和已有的改进数学形态学滤波,为该类降质图像的滤波增强处理提供了一条可供借鉴的思路。