Privacy self-correlation privacy-preserving scheme in LBS

The prevalence of mobile intelligent terminals gives the location-based service (LBS) more opportunities to enrich mobile users’ lives.However,mobile users enjoy the convenience with the cost of personal privacy.The side information and mobile user’s recent requirement records were considered,which were obtained or stored by the service provider.Based on the existence of recent requirement records,adversary can employ the inference attack to analysis mobile user’s personal information.Therefore,two schemes were proposed,including of basic privacy self-correlation privacy-preserving scheme (Ba-2PS) and enhanced privacy self-correlation privacy-preserving scheme(En-2PS).In En-2PS,the privacy-preserving scheme was designed from two dimensions of aspects of time factor and query region,which increased the uncertainty inferring out the real information.Finally,the privacy analysis was illustrated to proof En-2PS’s privacy degree,then the performance and privacy evaluation results indicate that En-2PS is effective and efficient.     

Bidirectional authentication key agreement protocol supporting identity’s privacy preservation based on RLWE

In order to solve the problem of identity privacy preservation between two participants involved when implementing authenticated key agreement protocol,a bidirectional authenticated key agreement protocol against quantum attack based on C commitment scheme was proposed.Through the design of C commitment function,the real identity information of two participants involved was hidden.Based on RLWE difficult problem,under the premise to ensure identity anonymity,this protocol not only completed two-way identity authentication,but also ensured the integrity of the transmitted message,furthermore,the shared session key was negotiated.After been analyzed,in terms of protocol’s execution efficiency,only two rounds of message transmission were needed to complete anonymous two-way authentication and key agreement in the proposed scheme.Compared with Ding’s protocol,the length of public key was reduced by nearly 50%.With regard to security,the protocol could resist forgery,replay,key-copy,and man-in-the-middle attacks.It is proved that the proposed protocol satisfies the provable security under the eCK model.At the same time,the protocol is based on the RLWE problem of lattices,and can resist quantum computing attacks.     

Mass transfer during osmotic dehydration of pineapple rings

The effect of temperature (30, 40 and 50°C) and sucrose concentration (50, 60 and 70°Brix) on the osmotic dehydration of commercial size pineapple rings were studied, at an initial ratio of 1:4 fruit:sucrose solution. The rate of water loss in the fruit varied with both osmotic solution concentration and temperature. A proposed model based on Crank's equation was fitted to the experimental data.     

基于差分隐私模型的位置轨迹发布技术研究

位置轨迹大数据的安全分享、发布需求离不开位置轨迹隐私保护技术支持。在差分隐私出现之前,K-匿名及其衍生模型为位置轨迹隐私保护提供了一种量化评估的手段,但其安全性严重依赖于攻击者所掌握的背景知识,当有新的攻击出现时模型无法提供完善的隐私保护。差分隐私技术的出现有效地弥补了上述问题,越来越多地应用于轨迹数据隐私发布领域中。该文对基于差分隐私理论的轨迹隐私保护技术进行了研究与分析,重点介绍了差分隐私模型下位置直方图、轨迹直方图等空间统计数据发布方法,差分隐私模型下轨迹数据集发布方法,以及连续轨迹实时发布隐私保护模型。与此同时,在对现有方法对比分析的基础上,提出了未来的重点发展方向。

     

面向物联网隐私数据分析的分布式弹性网络回归学习算法

为了解决基于集中式算法的传统物联网数据分析处理方式易引发网络带宽压力过大、延迟过高以及数据隐私安全等问题,该文针对弹性网络回归这一典型的线性回归模型,提出一种面向物联网(IoT)的分布式学习算法。该算法基于交替方向乘子法(ADMM),将弹性网络回归目标优化问题分解为多个能够由物联网节点利用本地数据进行独立求解的子问题。不同于传统的集中式算法,该算法并不要求物联网节点将隐私数据上传至服务器进行训练,而仅仅传递本地训练的中间参数,再由服务器进行简单整合,以这样的协作方式经过多轮迭代获得最终结果。基于两个典型数据集的实验结果表明：该算法能够在几十轮迭代内快速收敛到最优解。相比于由单个节点独立训练模型的本地化算法,该算法提高了模型结果的有效性和准确性;相比于集中式算法,该算法在确保计算准确性和可扩展性的同时,可有效地保护个体隐私数据的安全性。     

基于亮度保持的子图像加权对比度增强

本文提出了一种有效的基于亮度保持对比度增强算法.利用BBHE(brightness preserving bi-histogram equalization)算法产生的两个子图像,对两个子图像进行加权求和,从而得到输出图像.同时,根据输入图像以及两个子图像的亮度均值,给出了一种基于亮度保持的权重系数的计算方法.实验结果表明,与其它亮度保持对比度增强算法相比,本文算法能够更准确地保持输入图像的亮度均值以及较好地实现对比度增强.另外,本文算法计算简单,能够满足实时性的要求.     

High energy‐efficient and privacy‐preserving secure data aggregation for wireless sensor networks

An efficient data process technology is needed for wireless sensor networks composed of many sensors with constrained communication, computational, and memory resources. Data aggregation is presented as an efficient and significant method to reduce transmitted data and prolong lifetime for wireless sensor networks. Meanwhile, many applications require preserving privacy for secure data aggregation. In this paper, we propose a high energy‐efficient and privacy‐preserving scheme for secure data aggregation. Because of the importance of communication overhead and accuracy, our scheme achieves less communication overhead and higher data accuracy besides providing for privacy preservation. For extensive simulations, we evaluate and conclude the performance of our high energy‐efficient and privacy‐preserving scheme. The conclusion shows that the high energy‐efficient and privacy‐preserving scheme provides better privacy preservation and is more efficient than existing schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

An intelligent and privacy-enhanced data sharing strategy for blockchain-empowered Internet of Things

With the development of the Internet of Things (IoT), the massive data sharing between IoT devices improves the Quality of Service (QoS) and user experience in various IoT applications. However, data sharing may cause serious privacy leakages to data providers. To address this problem, in this study, data sharing is realized through model sharing, based on which a secure data sharing mechanism, called BP2P-FL, is proposed using peer-to-peer federated learning with the privacy protection of data providers. In addition, by introducing the blockchain to the data sharing, every training process is recorded to ensure that data providers offer high-quality data. For further privacy protection, the differential privacy technology is used to disturb the global data sharing model. The experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications.     

Edge preserving adaptive anisotropic diffusion filter approach for the suppression of impulse noise in images

This paper proposes a new anisotropic diffusion approach to remove the impulse noise and retain the fine details. The proposed approach contains two stages, the first stage detects the impulse noise, and the second stage removes the noisy pixel and retains the fine details of the original image. The Laplacian operator is used to fine-tune the image quality of the restored image in the anisotropic diffusion filter. The proposed approach is tested with PSNR, IEF, correlation factor, and NSER for different test images and the results are compared against existing algorithms. The simulation results show that the proposed approach gives better results than the existing denoising algorithms.     

川东南地区龙马溪组页岩“低电阻、低含气”成因及地质意义

为了明确五峰组—龙马溪组页岩“低电阻、低含气”成因,有效指导四川盆地下一步页岩气的勘探部署,依托全区大量钻井调查、解剖及分析化验测试结果,对问题开展了较为详细的研究。该区龙马溪组页岩低电阻率测井按其电性特征、地质特征的差异,可分为小于1 Ω·m和1~10 Ω·m两类。电阻率小于1 Ω·m的页岩气井基本不含气,以干井为主,分布区域相对集中,主要位于川西南、长宁西等地区;其电阻率曲线形态具“细脖子”特征,拉曼反射率普遍在3.70%以上且出现高幅度石墨峰;另外不同状态下岩电实验电阻值变化范围小,且均呈现极低—低电阻特征,说明石墨化造成的岩石骨架导电是影响该类页岩的主要原因。页岩电阻率在1~10 Ω·m范围的钻井分布区域较广,以微含气为主,在盆内、盆外均有分布,其电性、激光拉曼及岩电实验等表现出来的特征与电阻率小于1 Ω·m的页岩差异明显,页岩电阻率曲线具“渐变”特征,激光拉曼实测反射率在3.50% 左右,激光拉曼图谱也没有表现出明显的石墨峰特征。该类页岩进行烘干水及饱和水两种状态下的岩电实验变化范围大,即烘干前、后页岩电阻率变化在7~20倍,且呈现中—高电阻率特征,揭示页岩含水量对页岩电阻率有显著影响。结合实钻资料认为,页岩气保存条件变差、含水率增高是造成该类低阻井的主要原因。