AF型气氛保鲜纸常温保鲜苹果

采用ＡＦ型气氛保鲜纸对苹果进行了常温保鲜的效果试验,并与其他方法进行了对比试验。该法具有简单易行,投资少,见效快等特点。结果表明,用ＡＦ型气氛保鲜纸包裹苹果,在常温下能显著延长苹果的保藏期。     

NLDA non-linear regression model for preserving data privacy in wireless sensor networks

Recently, the application of Wireless Sensor Networks (WSNs) has been increasing rapidly. It requires privacy preserving data aggregation protocols to secure the data from compromises. Preserving privacy of the sensor data is a challenging task. This paper presents a non-linear regression-based data aggregation protocol for preserving privacy of the sensor data. The proposed protocol uses non-linear regression functions to represent the sensor data collected from the sensor nodes. Instead of sending the complete data to the cluster head, the sensor nodes only send the coefficients of the non-linear function. This will reduce the communication overhead of the network. The data aggregation is performed on the masked coefficients and the sink node is able to retrieve the approximated results over the aggregated data. The analysis of experiment results shows that the proposed protocol is able to minimize communication overhead, enhance data aggregation accuracy, and preserve data privacy.     

Brain MR image segmentation based on local Gaussian mixture model and nonlocal spatial regularization

Brain Magnetic Resonance (MR) images often suffer from the inhomogeneous intensities caused by the bias field and heavy noise. The most widely used image segmentation algorithms, which typically rely on the homogeneity of image intensities in different regions, often fail to provide accurate segmentation results due to the existence of bias field and heavy noise. This paper proposes a novel variational approach for brain image segmentation with simultaneous bias correction. We define an energy functional with a local data fitting term and a nonlocal spatial regularization term. The local data fitting term is based on the idea of local Gaussian mixture model (LGMM), which locally models the distribution of each tissue by a linear combination of Gaussian function. By the LGMM, the bias field function in an additive form is embedded to the energy functional, which is helpful for eliminating the influence of the intensity inhomogeneity. For reducing the influence of noise and getting a smooth segmentation, the nonlocal spatial regularization is drawn upon, which is good at preserving fine structures in brain images. Experiments performed on simulated as well as real MR brain data and comparisons with other related methods are given to demonstrate the effectiveness of the proposed method.     

Privacy management of patient physiological parameters

Patient Physiological Parameters (PPPs) seem to be the most extensively accessed and utilized Personal Health Information (PHI) in hospitals, and their utilization by the various medical entities for treatment and diagnosis creates a real threat to patient privacy. This study aims to investigate whether PPPs access in a hospital environment violates patient privacy. If so, to what extent can we manage patient privacy while accessing PPPs in this environment? We investigated this question by analyzing questionnaire-based data from two Asian countries: Group A (China) and Group B (Pakistan). For data collection, we targeted those medical entities which were directly dealing with PPPs in their routine tasks. Results suggest that patient type directly influences the collection of PPPs: Group A (one-time?=?1.9, follow-up?=?1.06) and Group B (one-time?=?2.0 and follow-up?=?1.9). Both groups agreed that patients have the right to control their own PPPs. In both, doctors are the most trusted entity: for Group A, the Pearson Chi-Square with one degree of freedom is 1.414, p?=?0.234, whereas for Group B, the Pearson Chi-Square with three degrees of freedom is 4.511, p?=?0.11. Most of the Group A entities (92%) are familiar with unauthorized access of PPPs, while in Group B the level was only 35%. In Group B, only 35% of entities stated the purpose, specification and use limitations of PPPs. Doctors in both groups showed a high utilization of PPPs read authorization rights. This empirical evidence about PPPs usage in both countries will benefit health technology and improve policy on patient privacy.     

Potential pitfalls of smart city development: A study on parking mobile applications (apps) in Hong Kong

Smart cities are built upon information and communication technologies (ICTs) to enable a broad range of advanced services. Through a comprehensive literature review, this study identified four pitfalls brought by the pervasive application of ICT, including information insecurity, privacy leakage, information islands, and digital divide. Therefore, a questionnaire survey together with 27 interviews was conducted in Hong Kong to investigate how the public perceived these pitfalls within the context of mobile apps providing real-time parking information which form a major part of smart mobility. System insecurity and privacy leakage were found to arouse worries among the app-users while their awareness of protecting personal data was found to have room for improvement. Islands of real-time parking information occur as a result of the lack of collaboration among private carpark operators. Digital divide existed widely among the disadvantaged groups and the problem cannot be solved by mere provision of ICT facilities. Overall, technologies alone cannot make a city smart or smarter. It is the suitable way in which ICTs are used to serve all citizens that matters.     

Search me if you can: Multiple mix zones with location privacy protection for mapping services

The mobile vehicle is gaining popularity nowadays using map services like Google Maps and other mapping services. However, map services users have to expose sensitive information like geographic locations (GPS coordinates) or address to personal privacy concerns as users share their locations and queries to obtain desired services. Existing mix zones location privacy protection methods are most general purposed and theoretical value while not applicable when applied to provide location privacy for map service users. In this paper, we present new (multiple mix zones location privacy protection) MMLPP method specially designed for map services on mobile vehicles over the road network. This method enables mobile vehicle users to query a route between 2 endpoints on the map, without revealing any confidential location and queries information. The basic idea is to strategically endpoints to nearby ones, such that (1) the semantic meanings encoded in these endpoints (eg, their GPS coordinates) change much, ie, location privacy is protected; (2) the routes returned by map services little change, ie, services usability are maintained. Specifically, a mobile client first privately retrieves point of interest close to the original endpoints, and then selects 2 points of interest as the shifted endpoints satisfying the property of geoindistinguishability. We evaluate our MMLPP approach road network application for GTMobiSim on different scales of map services and conduct experiments with real traces. Results show that MMLPP strikes a good balance between location privacy and service usability.     

User location privacy protection mechanism for location-based services

With the rapid development of the Internet of Things (IoT), Location-Based Services (LBS) are becoming more and more popular. However, for the users being served, how to protect their location privacy has become a growing concern. This has led to great difficulty in establishing trust between the users and the service providers, hindering the development of LBS for more comprehensive functions. In this paper, we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem. This mechanism not only guarantees the confidentiality of the user’s information during the subsequent information interaction and dynamic data transmission, but also meets the service provider’s requirements for related data.     

Research on LBS privacy preservation based on pseudorandom permutation in road network

A method of privacy preservation based on pseudorandom permutation was put forward for the issues of location privacy and query content privacy.Firstly,the distribution information of points of interest (PoI) based on the vertexes in the road network was organized,each single road vertex was taken as the foundational processing object.Based on the pseudorandom permutation,a permutation scheme of the point-of-interest records at the LBS server's end was put forward,a 32-bit random seed was adopted to generate a permuted table in the scheme,and the point-of-interest records were encrypted and permuted according to the table.These processed records were stored in the LBS database.Then a trusted intermediate server,replacing of the user,issued a query request with a record number instead of the query content to the LBS server.The LBS server could not determine which kind of PoI the user was interested in or which road section the user was locating on,and therefore the scheme achieved private information retrieval.Finally,the efficiency in the metrics of query accuracy,communication overhead and processing time was also analyzed.By the performance analysis and extensive experiments,the proposed scheme is proved to be location untraceable and query content uncorrelation.     

IoT/CPS的安全体系结构及关键技术

物联网（IoT）和信息物理融合系统（CPS）作为下一代网络的核心技术,被业界广泛关注。与传统网络不同,IoT/CPS异构融合、协同自治、开放互连的网络特性带来了巨大的系统安全方面的挑战。挑战包括安全协议的无缝衔接、用户隐私保护等。研发新的安全模型、关键安全技术和方法是IoT/CPS发展中的重点。文章基于IoT/CPS安全需求和威胁模型,提出了一种层次化的安全体系结构,并针对隐私保护、跨网认证和安全控制等IoT/CPS的关键安全技术展开讨论。     

TMWSNs中一种确保数据完整性的高能效时空Top-k查询协议

时空Top-k查询是TMWSNs（双层移动无线传感网）中的一类重要查询.在敌对环境中,攻击者易通过捕获TMWSNs中的关键节点来破坏时空Top-k查询的数据完整性.提出一种确保数据完整性的时空Top-k查询处理协议VIP-TQ.该协议利用虚拟化节点技术与绑定加密技术通过构建传感器节点的数据预处理方法、数据存储节点的时空Top-k查询处理方法以及Sink端的数据完整性验证方法来实现TMWSNs中时空Top-k查询的数据完整性保护.理论分析和实验结果显示,VIP-TQ能够以100%的概率侦测出不完整的时空Top-k查询结果,并具有相对已有方案更高的能效性.