Garbled computation in cloud

With the wide adoption of cloud computing paradigm, it is important to develop appropriate techniques to protect client data privacy in the cloud. Encryption is one of the major techniques that could be used to achieve this gaol. However, data encryption at the rest along is insufficient for secure cloud computation environments. Further efficient techniques for carrying out computation over encrypted data are also required. Fully homomorphic encryption (FHE) and garbled circuits are naturally used to process encrypted data without leaking any information about the data. However, existing FHE schemes are inefficient for processing large amount of data in cloud and garbled circuits are one time programs and cannot be reused. Using modern technologies such as FHE, several authors have developed reusable garbled circuit techniques in recent years. But they are not efficient either and could not be deployed at a large scale. By relaxing the privacy definition from perfect forward secrecy to all-or-nothing privacy, we are able to design efficient reusable garbled circuits in this paper. These reusable garbled computation techniques could be used for processing encrypted cloud data efficiently.     

面向用户隐私保护的高效基因比对方案

针对当前的基因序列比对协议普遍要求一个可信赖的第三方,可能因此造成大范围的隐私数据泄漏的问题,提出了一种基于线性扫描的基因比对方案。首先对两方的基因序列进行基于混淆电路（GC）的编码,然后线性扫描整个基因组数据库并用混淆电路实现客户的基因序列与库中所有基因序列的比对。上述方案可以在保护双方用户隐私的前提下,实现基因比对。不过该方案需要扫描整个基因组数据库,时间复杂度为O（n）,在基因组数据库较大时效率较低。为了提高基因比对的效率,进一步提出了基于不经意随机存取（ORAM）的基因比对方案,先将基因数据存储在ORAM上,然后只需把目标路径上的数据项取出并用混淆电路进行基因比对。该方案的比对次数和数据库的大小呈亚线性关系,时间复杂度为O（log n）。实验结果表明,基于ORAM的基因比对方案在实现隐私保护的同时,把比对次数由O（n）减小到了O（log n）,明显降低了比对操作的时间复杂度,可以用来进行疾病诊断,尤其适用于基因组数据库较大的场景。     

Java环境下Web程序的中文乱码问题与对策

由于目前JSP技术本身以及基于Java技术的某些开源软件的不完善,在Web程序设计过程中会出现很多问题,比如:JSP文件的中文乱码现象、数据库的中文乱码现象、文件名的乱码现象等.这些问题处理不好,会在很大程度上影响程序的开发与部署.针对目前构建Web程序常用到的环境Jdk+Tomcat5.0+ MySglserver5...     

JavaWeb应用中文乱码的解决方案

分析了Java Web应用中产生中文乱码的原因,归纳总结了产生中文乱码的几种情况,根据每种情况给出了多种解决方案,并分析了每种解决方案各自的优缺点以及适用场合,为Java Web程序员提供了参考和借鉴。