Fine-grained and heterogeneous proxy re-encryption for secure cloud storage

Cloud is an emerging computing paradigm. It has drawn extensive attention from both academia and industry. But its security issues have been considered as a critical obstacle in its rapid development. When data owners store their data as plaintext in cloud, they lose the security of their cloud data due to the arbitrary accessibility, specially accessed by the un-trusted cloud. In order to protect the confidentiality of data owners＇ cloud data, a promising idea is to encrypt data by data owners before storing them in cloud. However, the straightforward employment of the traditional encryption algorithms can not solve the problem well, since it is hard for data owners to manage their private keys, if they want to securely share their cloud data with others in a fine-grained manner. In this paper, we propose a fine-grained and heterogeneous proxy re-encryption （FH- PRE） system to protect the confidentiality of data owners＇ cloud data. By applying the FH-PRE system in cloud, data owners＇ cloud data can be securely stored in cloud and shared in a fine-grained manner. Moreover, the heteroge- neity support makes our FH-PRE system more efficient than the previous work. Additionally, it provides the secure data sharing between two heterogeneous cloud systems, which are equipped with different cryptographic primitives.     

Data Reduction and Triangulation Approach to Scattered Points

For the generation of the model in reverse engineering, a laser scanner is currently used a lot due to the fast measuring speed and high precision. Direct triangulation of data points captured from a physical object has a great advantage in that it can reduce the time and error in modeling process. It is important to reduce the number of data points for triangulating points with maintaining precision. To triangulate data points within a tolerance ε a new approach is developed in this paper. Different level of triangulations can be generated directly from data points using the proposed strategy that reduces and triangulates data points based on triangulation of 3D parametric surfaces. An experimental example is presented to demonstrate the effectiveness and efficiency of the proposed algorithm.     

Feature Preserving Milli-Scaling of Large Format Visualizations

Ultra-scale data analysis has created many new challenges for visualization.For example,in climate research with two-dimensional time-varying data,scientists find it crucial to study the hidden temporal relationships from a set of large scale images,whose resolutions are much higher than that of general computer monitors.When scientists can only visualize a small portion(< 1=1000) of a time step at one time,it is extremely challenging to analyze the temporal features from multiple time steps.As this problem cannot be simply solved with interaction or display technologies,this paper presents a milli-scaling approach by designing downscaling algorithms with significant ratios.Our approach can produce readable-sized images of multiple ultra-scale visualizations,while preserving important data features and temporal relationships.Using the climate visualization as the testing application,we demonstrate that our approach provides a new tool for users to effectively make sense of multiple,large-format visualizations.     

Digital Multi-Signature Based on the Controlled Quantum Teleportation

In this paper, a scheme which can be used in multi-user quantum digital signature is proposed. The scheme of signature and verification is based on the characters of GHZ （Greenberger-Horne-Zeilinger） states and controlled quantum teleportation. Different from the digital signatures based on computational complexity, this scheme is unconditional secure, and compared to the former presented quantum signature scheme, it does not rely on an arbitrator to verify the signature and realize a message can be signed by multi-user together.     

Warped time lens in temporal imaging for optical real-time data compression

We introduce for the first time the concept of anamorphic temporal imaging and its application to analog data compression in a time lens. Placed in front of a conventional spectrometer, this technique enhances the spectral resolution and the update rate. More importantly, it performs real-time optical data compression to reduce the volume of the generated digital data. Our technique introduces the concept of the warped time lens. We show that a specific class of warped time-to-frequency mapping operations combined with the nonlinear operation inherent in a photo-detector compresses the time-bandwidth product in a temporal imaging system. We employ our newly introduced Stretched Modulation Distribution to design the warp profile. Using this method, the narrow spectral features beyond the spectrometer resolution can be captured and at the same time the output bandwidth and hence the record length is minimized. The reduction in the record length results in higher update rate for the spectrometer without sacrificing the spectral resolution or bandwidth. Our method also benefits from amplitude and phase detection to recover the input complexfield spectrum. By compressing the time-bandwidth product, anamorphictemporal imaging addresses the Big Data problem in such highthroughput instruments.     

Secure Scheme for Locating Disease-Causing Genes Based on Multi-Key Homomorphic Encryption

Genes have great significance for the prevention and treatment of some diseases. A vital consideration is the need to find a way to locate pathogenic genes by analyzing the genetic data obtained from different medical institutions while protecting the privacy of patients’ genetic data. In this paper, we present a secure scheme for locating disease-causing genes based on Multi-Key Homomorphic Encryption(MKHE), which reduces the risk of leaking genetic data. First, we combine MKHE with a frequency...     

MICkNN: Multi-Instance Covering kNN Algorithm

Mining from ambiguous data is very important in data mining. This paper discusses one of the tasks for mining from ambiguous data known as multi-instance problem. In multi-instance problem, each pattern is a labeled bag that consists of a number of unlabeled instances. A bag is negative if all instances in it are negative. A bag is positive if it has at least one positive instance. Because the instances in the positive bag are not labeled, each positive bag is an ambiguous. The mining aim is to classify unseen bags. The main idea of existing multi-instance algorithms is to find true positive instances in positive bags and convert the multi-instance problem to the supervised problem, and get the labels of test bags according to predict the labels of unknown instances. In this paper, we aim at mining the multi-instance data from another point of view, i.e., excluding the false positive instances in positive bags and predicting the label of an entire unknown bag. We propose an algorithm called Multi-Instance Covering kNN (MICkNN) for mining from multi-instance data. Briefly, constructive covering algorithm is utilized to restructure the structure of the original multi-instance data at first. Then, the kNN algorithm is applied to discriminate the false positive instances. In the test stage, we label the tested bag directly according to the similarity between the unseen bag and sphere neighbors obtained from last two steps. Experimental results demonstrate the proposed algorithm is competitive with most of the state-of-the-art multi-instance methods both in classification accuracy and running time.     

Computer recognition of slag property diagrams in ternary systems

In order to take data information from the slag property diagram in a ternary system automatically and actually, a picture recognition and drawing software has been developed by Visual Basic 6.0 based on the image coding principle of computer system and the graphics programming method of VB. This software can transform the ternary system isopleth diagram from bitmap format to data file and establish a corresponding database which can be applied to rapidly retrieve a mass of data and make correlative thermodynamics or kinetics calculation. Besides, it still has the function of drawing the ternary system diagram which can draw different kinds of property parameters in the same diagram.     

The time-saving numerical method for GPS/MET observation operator

The global positioning system (GPS) ray-shooting method is a self-sufficient observation operator inGPS/MET (meteorology) data variational assimilation linking up the GPS observation data and the atmosphere state vari-ables. But it cannot be applied to data assimilation and operational prediction so far because of huge computations. In order to reduce the amount of computation, a 2-order time-saving symplectic scheme is used to solve the equations of the GPS ray trajectory, due to its separable Hamiltonian nature, and good results are achieved. Not only does it save 75 % of CPU time taken by the old GPS ray-shooting model with 4th-order Runge-Kutta method , but also it improves the sim-ulation accuracy to some extent.     

深入Java~(TM)2安全模型体系结构

Java2平台作为当今软件开发的主流工具,不仅具有良好的面向对象特性和平台可移植性,还具有一个非常重要的特性:安全性。它不仅为用户和开发人员提供了一个安全平台而且还提供了丰富的安全API和安全工具。本文着重介绍Java2平台的安全体系结构部分,在揭示Java2平台安全原理的同时,介绍了如何利用Java2平台的安全机制来保证系统的安全性。     

可逆式JPEG 数据隐藏

针对数字化图像文档因随着数字相机像素质量的提升而变大,使其在网络传输过程中耗费更多传输时间的问题,提出了一种结合JPEG (Joint Picture Experts Group)数据压缩的可逆式隐藏技术,运用该技术可缩短影像传输的时间并且在影像传输的同时可传达隐藏的秘密数据.实验结果证明,文中所提技术可成功实现具有压缩的可逆式数据隐藏.     

基于互联网的过程控制系统的安全性设计

分析了远程控制系统安全性设计要解决的两个方面问题：为防止未授权用户恶意破坏控制系统,提出了对付网络入侵者恶意操作控制系统的安全措施;为保证实时数据传输的快速性和安全性,将高级数据加密标准AES与网络通信加密协议SSL相结合,实现了适合于实时控制系统的数据加密算法,并通过测量实时数据加密传输的网络时延来验证该算法的有效性．     

Secure Sensitive Data Sharing on a Big Data Platform

Users store vast amounts of sensitive data on a big data platform. Sharing sensitive data will help enterprises reduce the cost of providing users with personalized services and provide value-added data services.However, secure data sharing is problematic. This paper proposes a framework for secure sensitive data sharing on a big data platform, including secure data delivery, storage, usage, and destruction on a semi-trusted big data sharing platform. We present a proxy re-encryption algorithm based on heterogeneous ciphertext transformation and a user process protection method based on a virtual machine monitor, which provides support for the realization of system functions. The framework protects the security of users' sensitive data effectively and shares these data safely. At the same time, data owners retain complete control of their own data in a sound environment for modern Internet information security.     

基于AODV的Ad Hoc网络安全高效双路由机制

提出了一种基于AODV的安全、高效双路由协议。在充分考虑网络资源和均衡流量的同时,采用双路由传输信息并利用密钥协商协议增强路由信息安全性和机密性。仿真结果表明,这种机制能够延长网络的生存时间,提高包传输率,具有较好的安全性。     

基于代理重加密的VANETs中安全位置服务

提供车辆位置服务是车载网络(vehicle ad hoc networks, VANETs)的重要应用。而用户(车辆行驶人)希望他的位置信息只能暴露于他授权的消息发送者,这就涉及位置隐私问题。提出基于代理重加密的安全位置服务算法(proxy re-encryption- based secure location service, PRESLS)。PRESLS算法采用中心管理模式,并由交通信息港(traffic information center, TIC)扮演中心管理者,且由TIC维持车辆轨迹数据,同时,TIC作为车辆与路边设施单元的中介,使得路边设施单元能安全地共享轨迹数据。利用代理重加密算法,使得轨迹数据不仅对未授权的实体,而且对TIC也是隐匿的,进而实现了位置数据所保密性。通过安全性能分析和基于地图位置服务(map-based location service, MBLS)的实验评估PRESLS算法的性能。分析表明,车辆能够控制仅由车辆允可的路边设施单元才能接入车辆的轨迹数据。同时,基于MBLS的实验数据表明,PRESLS算法在维持车辆轨迹数据安全的同时,并没有降低位置查询成功率。     

IPv6的IP封装安全性的有效负载

对下一代互联网络协议-IPv6的IP封装的安全性的有效负载（ESP）进行了全面深入的分析,对其分组格式及实现过程进行了详细的讨论,研究了ESP在传送模式和隧道模式下的典型实现方案,并结合AH机制给出了一个典型的安全网络方案,该方案对于在IPv6网络环境下构建一个安全的网络应用具有一定的应用价值.     

基于脉冲控制理论的时滞混沌系统同步技术研究进展

基于脉冲控制理论的时滞混沌系统同步的保密通信方案具有更高的保密性、更大的信息处理能力和存储容量,具有更强的鲁棒性等优点,应用的前景巨大。深入分析了理想环境和复杂环境下时滞混沌系统脉冲同步控制技术的研究现状,指出了其目前存在的问题和发展趋势。     

一种基于安全索引的位置隐私保护方法

基于位置的服务(location based services, LBS)为人们日常生活带来极大便利的同时也严重地威胁到用户的隐私.为了在保护用户位置隐私的同时降低用户的查询代价,提出了一种基于安全索引的位置隐私保护方法(location privacy protection method based on secure index, LPPMSI).LPPMSI不需要用户搜集数据信息,数据拥有者为虚假位置信息建立安全索引.用户能够安全、快速地检索到虚假位置信息,服务器再执行基于虚假位置的LBS.并且还提出了基于滑动窗口的候选位置选择算法,有效减少候选位置选择时间.实验结果表明,LPPMSI在不改变隐私保护能力的前提下,不需要用户花费大量时间搜集数据分布及查询概率信息.