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Private information retrieval(PIR) is an important privacy protection issue of secure multi-party computation, but the PIR protocols based on classical cryptography are vulnerable because of new technologies,such as quantum computing and cloud computing. The quantum private queries(QPQ) protocols available, however, has a high complexity and is inefficient in the face of large database. This paper, based on the QKD technology which is mature now, proposes a novel QPQ protocol utilizing the key dilution and auxiliary parameter. Only N quits are required to be sent in the quantum channel to generate the raw key, then the straight k bits in the raw key are added bitwise to dilute the raw key, and a final key is consequently obtained to encrypt the database. By flexible adjusting of auxiliary parameters θ and k, privacy is secured and the query success ratio is improved. Feasibility and performance analyses indicate that the protocol has a high success ratio in first-trial query and is easy to implement, and that the communication complexity of O(N) is achieved. 相似文献
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在目前数据爆炸、信息匮乏的情况下,需要利用数据仓库系统集成1个或多个独立传统数据库数据,通过分析海量数据发现市场潜在规律,获取商业信息以支持商业决策,这将是广电未来的制胜武器。 相似文献
6.
实时数据管理系统是流程企业控制信息网络与管理信息网络平滑集成的基础,为两者的数据通讯提供桥梁。介绍了笔者在炼油化工C企业IMS建设中的实时数据管理引擎设计与开发,具有其先进性与实用性。 相似文献
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地理信息系统的应用越来越广泛,特别是基于网络的GIS的发展使地理空间信息通过网络被多用户所共享,因此必须考虑地理数据访问的安全性。文章以MapInfoSpatailWare空间数据引擎为研究对象,给出了基于此模式的数据访问安全性解决方案。 相似文献
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异构数据集成方法研究与实现 总被引:4,自引:4,他引:0
王行荣 《微电子学与计算机》2006,23(4):172-173,176
为解决异构数据集成的复杂性问题,文章提出了一种异构数据同步的新方法——半集成式中间件法。该方法成功地应用在重庆市社会保障综合信息系统中,具有易于实现、可扩展性、跨平台性和效率高等特点。 相似文献
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Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional
groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal
activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on
the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three
principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that
may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional
rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore
models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation
adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and
multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting
medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric
models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual
medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures
as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for
activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in
some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically,
using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct
good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments
in statistical relational learning.
Editors: Tamás Horváth and Akihiro Yamamoto 相似文献