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On Mutual Support of Modern and Traditional Access Control Models with UCON and BLP as Case Study

On Mutual Support of Modern and Traditional Access Control M...

引用

WRI International Conference on Communications and Mobile Computing, CMC

作者： Hui Feng Wenchang Shi Zhaohui Liang Bin Liang School of Information Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing China

Access control is essential to computer security, especially in an open, distributed, networked communication environment. Modern access control model such as UCON aims at accommodating general requirements. Traditional one such as BLP focuses on specific properties, e.g. confidentiality. Both of these two realms have their limitations. Taking UCON and BLP as case study, this paper explores mutual support of modern and traditional access control models. It investigates BLP's adaptable characteristic in the UCON perspective. First, it constructs properties in the UCON language to manifest the BLP adaptability, which shows that the BLP adaptability can be ensured to function correctly by the UCON framework. Further, it proposes a formal specification for the BLP adaptability under the UCON framework with the Temporal Logic of Actions, which demonstrates that the BLP adaptability is in good consistency with the UCON model. The significance of the paper is twofold. On the one hand, it exhibits that adaptable quality of the traditional BLP model may be ensured theoretically by the philosophy of modern access control. On the other hand, it enriches the real sense of modern access control models by strengthening the power of traditional access control models.

关键词： Adaptation model Sensitivity Authorization Permission Computational modeling

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图形处理器加速的联机分析处理系统

图形处理器加速的联机分析处理系统

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第29届中国数据库学术会议

作者： Fang Yixuan 方艺璇刘虹 Liu Hong Chen Hong 陈红 Li Cuiping 李翠平 Zhang Yansong 张延松 Zhao Suyun 赵素云 Chen Jie 陈杰辛鑫 Xin Xin Zhang Ji 张吉 Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) Ministry 数据工程与知识工程教育部重点实验室(中国人民大学) 北京100872 中国人民大学信息学院北京100872 Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) Ministry 数据工程与知识工程教育部重点实验室(中国人民大学) 北京100872 中国人民大学中国调查与数据中心北京100872

基于现有联机分析处理系统(online analytical processing,OLAP)的不足和图形处理器(graphics processing unit,GPU)的发展,研制了GOOLAP(GPU oriented OLAP)系统.GOOLAP系统利用GPU的高并行性和高存储带宽,把计算密集型运算转移到GPU端执行,加运OLAP处理性能.GOOLAP系统主要由3部分组成：1)表示层,以Excel作为用户输入前端并展示结果,加强系统的易用性;2)OLAP服务器层,负责把多维表达式(multi-dimensional expression,MDX)语句解析成SQL语句并根据自定义启发式规则向GPU传递适合计算的SQL语句,最后再将GPU返回结果与CPU原始结果合并;3)存储层,提供GPU显存和关系数据库两种存储结构.

关键词：图形处理器联机分析处理系统优化设计功能模块

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MyBUD自适应分布式存储管理的设计与实现

MyBUD自适应分布式存储管理的设计与实现

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第29届中国数据库学术会议

作者： ZHOU Ningnan 周宁南 ZHANG Xiao 张孝 SUN Xinyun 孙新云 JU Xingxing 琚星星 LIU Kuicheng 刘奎呈 DU Xiaoyong 杜小勇 WANG Shan 王珊 Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin Universi 中国人民大学数据工程与知识工程教育部重点实验室北京100872 中国人民大学信息学院北京100872

面对日益增长的非结构化数据管理需求，实现了基于“自由表”数据模型和BUD参考体系模型的非结构化数据管理平台MyBUD系统。提出了一种能够根据非结构化数据的类型和访问特点自适应地选择分布式存储子系统的方法，同时也对MyBUD进行了T... 详细信息

面对日益增长的非结构化数据管理需求，实现了基于“自由表”数据模型和BUD参考体系模型的非结构化数据管理平台MyBUD系统。提出了一种能够根据非结构化数据的类型和访问特点自适应地选择分布式存储子系统的方法，同时也对MyBUD进行了TPCC测试和非结构化数据存取实验。结果表明，这种自适应的数据存储方法为MyBUD系统提供了高效的可扩展存储层，为采用数据库方法实现对结构化和非结构化数据统一管理的进一步研究工作奠定了基础。

关键词：数据库系统存储管理自适应算法体系架构服务质量

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Analysis of bandwagon and average hybrid attack model against trust-based recommender systems

Analysis of bandwagon and average hybrid attack model agains...

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2011 International Conference on Management of e-Commerce and e-Government, ICMeCG 2011

作者： Zhang, Fuguo School of Information and Technology Jiangxi University of Finance and Economics Nanchang China Institute of Information Resource Management Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9780769545448

Recommender systems have been accepted as a vital application on the web by offering product advice or information that users might be interested in. Despite its success, similarity-based collaborative filtering suffers from some significant limitations, such as scalability, sparsity and recommendation attack. Prior work has shown incorporating trust mechanism into traditional collaborative filtering recommender systems can improve these limitations. However, trust-based recommender systems are also known to be vulnerable to profile infection attacks. Malicious users can inject a large number of biased profiles into such a system in order to make recommendations that favor or disfavor given items. In this paper, we propose a bandwagon and average hybrid attack model and analysis the effectiveness of the attack model against topic-level trust-based recommender algorithm. The results of our experiments conducted on well-known dataset show that the hybrid attack model is more effective than other attack models. © 2011 IEEE.

关键词： Recommender systems

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Sentiment classification via L2-norm deep belief network 11

Sentiment classification via L2-norm deep belief network

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20th ACM Conference on Information and knowledge Management, CIKM'11

作者： Liu, Tao Li, Minghui Zhou, Shusen Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering MOE 100872 Beijing China School of Information Renmin University of China 100872 Beijing China Microsoft Asian Research and Development Group 100080 Beijing China Shenzhen Graduate School Harbin Institute of Technology 518055 Shenzhen China

ISBN: (纸本)9781450307178

Automatic analysis of sentiments expressed in large scale online reviews is very important for intelligent business applications. Sentiment classification is the most popular task of sentiment analysis, which is more challenging than traditional topic-based text classification. Basic features, such as vocabulary words, are not enough to classify sentiments well. Deep Belief Network (DBN) is introduced to discover more abstract features of sentiments. To capture full information of the features, large-size network can be constructed, but at the same time, large-size network tends to over fit the training data and even noise, which will reduce the generalization ability of the network. In this paper, L2-norm Deep Belief Network (L2DBN) is proposed, which uses L2-norm regularization to optimize the network parameters of DBN. L2DBN is first initialized by an unsupervised layer-wise training algorithm, and then fine-tuned by a supervised procedure. Network parameters are optimized using both classification loss and network complexity. Experimental results show that the proposed L2DBN outperforms the state-of-the-art method and the basic DBN on golden, noisy and heterogeneous datasets. © 2011 ACM.

关键词： Sentiment analysis

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Lawyer information integration and recommendation by multi-source information validation

Lawyer information integration and recommendation by multi-s...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tao Liu Biao Fan He Hu Xiao-Yong Du Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China China School of Information Renmin University of China Beijing China

On the internet, all-round lawyer information is located at separated information sources, which prevent web users from effective information acquisition. In order to build a unified view of separated, heterogeneous, and often redundant lawyer information, we propose a new information integration method using multi-source information cross-validation. Based on the unified integrated data, a lawyer recommendation system is built. Several key technologies are presented and evaluated, including the multi-source information acquisition and validation. Experimental results indicate the key techniques used in the system are effective for lawyer information integration and recommendation.

关键词： Organizations Crawlers Search engines data mining Web pages databases Reliability

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Parallel Aggregation Queries over Star Schema: A Hierarchical Encoding Scheme and Efficient Percentile Computing as a Case

Parallel Aggregation Queries over Star Schema: A Hierarchica...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Xiongpai Qin Huiju Wang Xiaoyong Du Shan Wang Ministry of Education Key Laboratory of Data Engineering and Knowledge Engineering RUC Beijing China School of Information Renmin University of China Beijing China

Big data analysis is a main challenge we meet recently. Cloud computing is attracting more and more big data analysis applications, due to its well scalability and fault-tolerance. Some aggregation functions, like SUM, can be computed in parallel, because they satisfy distributive law of addition. Unfortunately, some of statistical functions are not naturally parallelizable. That means they do not satisfy distributive law of addition. In this paper, we focus on percentile computing problem. We proposed an iterative-style prediction-based parallel algorithm in a distributed system. Prediction is done through a sampling technique. Experiment results verify the efficiency of our algorithm.

关键词： Prediction algorithms Convergence Algorithm design and analysis Histograms Encoding Query processing Indexes

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Managing Electronic Records in E-government:Current Trends and Future Directions Internationally

Managing Electronic Records in E-government:Current Trends a...

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International Conference on Management and Service Science(2011年第五届管理与服务科学国际会议 MASS 2011)

作者： Xiaomi An Wei Zhang Shuyang Sun Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of School of Information Resources Management Renmin University of China Beijing China

More and more literature has been written on electronic records management (ERM) in e-government in recent three years, however, much is limited to experiences of one country with more focus on electronic records management systems (ERMS). This paper aims to investigate current trends and future directions of ERM including ERMS in e-government with more focus on comprehensive approaches internationally. Representative shows current ERMS have limitations either from IT perspectives or records and archives management perspectives managing records as data. Future research is called for more concerns of e-government and more involvement in efficient civil service. Case studies of representative policies, regulations, best practices guidelines from Australia, Canada, New Zealand, UK and U.S show challenges of ERM in e-government are getting more and more recognized in information risk, data governance and efficient civil service. Current trends of ERM in e-government are toward multidisciplinary and collaborative approaches to ERM managing records as information resources and business asset. Findings indicate that future directions of ERM in e-government would be toward meta-synthesis management at both organizational and national level, with integration concerns of collaboration, optimization and innovation of both ERM and e-government for civil service. The findings may have implications to be of use to both ERM and e-government professions internationally.

关键词： Electronic government Law Information services Collaboration

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A RFID Mixed Coding Scheme Based on Huffman Algorithm

A RFID Mixed Coding Scheme Based on Huffman Algorithm

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International Conference on Management of e-Commerce and e-Government, ICMECG

作者： Jiang Jian Liao Guoqiong Wang Hao Wan Qizhi School of Information Technology Jiangxi university of Finance and Economics China Jiangxi Key Laboratory of Data and Knowledge Engineering Nanchang Nanchang China

In RFID application systems with multiple packaging layers, labeling packaging relationship of objects in different packaging layers by encoding methods is a important technology field. Prefix-based labeling scheme is a method by which the packaging relationship of objects amounts to testing whether one object is an prefix of the other, whereas the region numbering scheme is a method by which an ancestor query amount to an interval containment test on the labels. This paper first presents a mixed-encoding scheme based on Huffman algorithm, then propose a variant of this encoding scheme in which new "virtual nodes" are involved in order to improve the stability of encoding. Our experiments prove that the mixed-based encoding scheme is effective due to the enhancement of update performance and query efficiency.

关键词： Encoding Labeling Radiofrequency identification XML Algorithm design and analysis Testing

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A decomposition method to solve the large-scale scheduling problems based on cellular manufacturing technology

A decomposition method to solve the large-scale scheduling p...

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International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC)

作者： Li Niu Xiaoting Han Data Engineering and Knowledge Engineering Key Laboratory School of Information Resource Management Renmin University of China Beijing China School of Economics and Management Beihang University Beijing China

A decomposition method to solve the large-scale scheduling problems is proposed in this paper. Focused on large-scale scheduling problems, introducing cellular manufacturing technology to decompose scheduling problems, a collaborative scheduling process based on manufacturing cells is designed. Moreover, focused on the coupling problem in scheduling process in the context of cellular manufacturing, a decomposition method is suggested to achieve the decomposition of cross-cell jobs. Finally, the whole scheduling process is simplified through redefining the environment of cellular manufacturing.

关键词： Job shop scheduling Cellular manufacturing Processor scheduling Computers Educational institutions Economics

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