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A cloaking-based approach to protect location privacy in location-based services 33

A cloaking-based approach to protect location privacy in loc...

引用

Proceedings of the 33rd Chinese Control Conference, CCC 2014

作者： Zheng, Jiangyu Tan, Xiaobin Zou, Cliff Niu, Yukun Zhu, Jin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230026 China Department of Automation University of Science and Technology of China Hefei230026 China Department of Electrical Engineering and Computer Science University of Central Florida OrlandoFL32816-2362 United States

ISBN: (纸本)9789881563842

With the widespread use of mobile devices, the location-based service (LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service (QoS), users are required to report their locations as accurate as possible. To achieve the dedicated tradeoff between privacy requirement and QoS requirement, we propose a novel approach based on cloaking technique. We also discuss the disadvantage of the traditional general system model and propose an improved model. The basic idea of our approach is to select a sub-area from the generated cloaking area as user's reported location. The sub-area may not contain a user's real location, which prevents an adversary from performing attack with side information. Specifically, by defining an objective function with a novel location privacy metric and a QoS metric, we are able to convert the privacy issue to an optimization problem. Then, location privacy metric and QoS metric are given. To reduce the complexity of the optimization, a heuristic algorithm is proposed. Through privacy-preserving analysis and comparison with related work [8], we demonstrate the effectiveness and efficiency of our approach. © 2014 TCCT, CAA.

关键词： Location based services

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The first algorithm for solving two coins counterfeiting with ω(ΔH) = ω(ΔL)

The first algorithm for solving two coins counterfeiting wit...

引用

International Conference on Electrical and computer engineering (ICECE)

作者： Joydeb Ghosh Arpan Chakraborty Piyali Datta Lagnashree Dey Ankita Nandy Rajat Kumar Pal Ranjit Kumar Samanta Department of Computer Science and Application North Bengal University Darjeeling West Bengal India Department of Computer Science and Engineering University of Calcutta Kolkata West Bengal India

Counterfeit coin problem is of utmost importance and it is truly interesting in computer science and Game theory as well as in Mathematics. In this problem the objective is to detect the fake coin(s) of identical appearance but of different weight in minimum number of comparisons. The word counterfeit is most frequently applicable to forgeries of currency or documents, but can also describe software, pharmaceuticals, clothing, and more recently, motorcycles and other vehicles, especially when these result in patent or trademark infringement. In this paper we have developed a new algorithm for solving two counterfeit coins problem in linear time, where n is the total number of coins given. However, this is the first algorithm that identifies and solves the problem, given the false coins with type ω(ΔH) = ω(ΔL), i.e., one false coin is heavier and another is lighter than a true coin, and their difference in weight from the true coin is equal. However, this is the degenerate case in the field of two counterfeit coins problem.

关键词： Patents Silicon carbide

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Comparative analysis of GA and SA for utility maximization of licensed and unlicensed users in a cognitive radio network

Comparative analysis of GA and SA for utility maximization o...

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International Conference on Control, Instrumentation, Energy and Communication (CIEC)

作者： Roukna Sengupta Subhasree Bhattacharjee Department of Computer Science and Engineering RCC Institute of Information Technology Kolkata India Department of Computer Application Narula Institute of Technology Kolkata India

In this paper we consider a cognitive radio network comprising of a number of primary users (PUs) and a number of secondary users (SUs). The spectrum has been divided into channels by means of frequency division multiple access (FDMA). The PUs have license to use the channels and the SUs periodically check the channels for idleness. When the channels are not in use by the PUs, the SUs may bid for them. The PUs auctions off the channels to the purchasers (SUs) who offer most money for them. Thus, PUs earn revenue in place of the spectrum. Here, we intend to compute an allocation of channels/vacant spectrums to the SUs such that the total revenue earned by all PUs is maximized. We also intend to compute another such allocation of channels/vacant spectrum to the SUs such that the payoff earned by the SUs is maximized. Both these optimizations have been performed with the help of real coded genetic algorithm (GA) and simulated annealing (SA) algorithm. We have made comparative analysis of both the algorithms and show that GA provides better near optimal solution compared to SA in terms of computation of a close to optimal solution. But, computational time of GA is more than that of SA. GA suffers from premature convergence, which can be dealt with SA.

关键词： Genetic algorithms Resource management Licenses Cognitive radio Optimization FCC Linear programming

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An endeavour to find two unequal false coins

An endeavour to find two unequal false coins

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International Conference on Electrical and computer engineering (ICECE)

作者： Joydeb Ghosh Piyali Datta Arpan Chakraborty Ankita Nandy Lagnashree Dey Rajat Kumar Pal Ranjit Kumar Samanta Department of Computer Science and Application North Bengal University Darjeeling West Bengal India Department of Computer Science and Engineering University of Calcutta Kolkata West Bengal India

The counterfeit coin problem is well-known and truly interesting in computer science, Game theory, and also in Mathematics. In this problem the objective is to detect the fake coin(s) of identical appearance but different weight in minimum number of comparisons. The word counterfeit most frequently describes forgeries of currency or documents, but can also describe software, pharmaceuticals, clothing, and more recently, motorcycles and cars, especially when these result in patent or trademark infringement. Finding one fake coin among n coins is tricky enough and complex. The problem becomes rigorous when there are two fake coins, as the false coin pair may form several different combinations that make the problem particularly tricky and complex to solve. In this paper we have developed a new algorithm for solving two versions of the two counterfeit coins problem in O(log n) time, where n is the number of coins given.

关键词： Games Automation

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Adaptive Semi-Supervised Dimensionality Reduction

Adaptive Semi-Supervised Dimensionality Reduction

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Jia Wei Jiabing Wang Qianli Ma Xuan Wang School of Computer Science and Engineering South China University of Technology Computer Application Research Center Harbin Institute of Technology Shenzhen Graduate School

ISBN: (纸本)9781479942732

With the rapid accumulation of high dimensional data, dimensionality reduction plays a more and more important role in practical data processing and analysing tasks. This paper studies semi-supervised dimensionality reduction using pair wise constraints. In this setting, domain knowledge is given in the form of pair wise constraints, which specifies whether a pair of instances belong to the same class (must-link constraint) or different classes (cannot-link constraint). In this paper, a novel semi-supervised dimensionality reduction method called Adaptive Semi-Supervised Dimensionality Reduction (ASSDR) is proposed, which can get the optimized low dimensional representation of the original data by adaptively adjusting the weights of the pair wise constraints and simultaneously optimizing the graph construction. Experiments on UCI classification and face recognition show that ASSDR is superior to many existing dimensionality reduction methods.

关键词： Equations Mathematical model Training Kernel Time complexity Face Databases

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Assessing Ancestral Genome Reconstruction Methods by Resampling

Assessing Ancestral Genome Reconstruction Methods by Resampl...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Jun Zhou Fei Hu William Hoskins Jijun Tang Department of Computer Science and Engineering University of South Carolina Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University

ISBN: (纸本)9781479956708

Inference of ancestral or extinct genomes is important in evolutionary biology, cancer research and many other research areas. Whole-genome data has become readily available due to advances in large-scale sequencing technology. During the past decades, a number of evolutionary models and related algorithms have been designed to infer ancestral genome sequence or gene order. Since it is so hard or even impossible to know the true scenario of the ancestral genomes, there must be some tools used to test the robustness of the adjacencies obtained from existing methods. However, till now, there is still no systematic work being conducted to tackle this problem. On the other hand, it is a common practice in phylogenetic analysis to assess the confidence rate of the inferred branches, using techniques such as bootstrapping and jackknifing, which have been evaluated as good resampling tools for phylogenetic reconstruction methods. Some of these resampling methods can be potentially used as a robustness test for ancestral genomes. In this paper, we conduct large-scale experiments by using three existing best ancestral genome inference methods and four different resampling techniques. Experimental results show that resampling techniques are useful for assessing the quality of ancestral genomes, while different methods have different preferred resampling techniques. It is suggested the cut-off threshold of 75% should be used to filter bad gene adjacencies.

关键词： Ancestral genome reconstruction Genome rearrangement Resampling

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A Systematic Study of OpenStreetMap Data Quality Assessment

A Systematic Study of OpenStreetMap Data Quality Assessment

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International Conference on Information Technology: New Generations (ITNG)

作者： Sukhjit Singh Sehra Jaiteg Singh Hardeep Singh Rai Dept of Computer Science& Engineering GNDEC Ludhiana Punjab India Department of Computer Application CIET Punjab India Dept of Civil Engineering GNDEC Ludhiana Punjab India

ISBN: (纸本)9781479931897

The evolution of web has changed the way of interaction with the user. Web 2.0 encouraged more contribution from the user of varying level of mapping experience and is called Crowd Sourcing. Open Street Map is also the outcome of Crowd Sourcing. It is collecting huge data with help of general public, researchers have started analysing the data rather than collecting it. The aim of this study is to review the research work for assessment of Open Street Map Data. It is concluded that the most of research work on assessment of Open Street map data has been done for countries like Germany, UK & USA. But the authenticity and accuracy of reference data still unanswered. Another issue that is concluded by this review, in context to Indian subcontinent, is the requirement of through analysis of Open Street Map data.

关键词： Accuracy Roads Internet Spatial databases Information services Electronic publishing Quality assessment

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Study on data security mechanism in cloud computing

Study on data security mechanism in cloud computing

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International Conference on Current Trends in engineering and Technology (ICCTET)

作者： Sandha M. Ganaga Durga Department of Computer Application St. Michael College of Engineering and Technology Kalayar Koil Department of Computer Science Government Arts College for Women Sivagangai

Data integrity protection in outsourced data is challenging task in cloud computing. Client or third party auditor need to check the integrity of outsourced data. For this purpose so many approaches are introduced with different types of algorithms such as Proof of Retrievablity, provable data possession, privacy preserving, etc. This extensive paper aims to make comparative analysis on RSA based homomorphic and BLS based homomorphic by time factor and produce the best algorithm for data protection as well as time consuming. Which is used to the cloud user choose the best mechanism based on their resource and requirements and help to make their integrity checking process effectively.

关键词： Cloud computing Conferences Algorithm design and analysis Software as a service Encryption Market research

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Performance analysis on agriculture ontology using SPARQL query system

Performance analysis on agriculture ontology using SPARQL qu...

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International Conference on Data Mining and Intelligent Computing (ICDMIC)

作者： Aditya Khamparia Babita Pandey Vikas Pardesi Department of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Department of Computer Application Lovely Professional University Phagwara Punjab India

Ontologies are used to represent domain knowledge with help of object, their behaviour and properties. This paper represents web enabled approach on agriculture semantic web using SPARQL and specified tools to increase productivity of farmers. This work focuses on assessment of query optimization tools and results predicted from them to determine the suitability of each method for different users where structured ontologies are used as querying aids for agriculture based dataset.

关键词： Ontologies Agriculture Diseases Resource description framework Knowledge based systems Information retrieval

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Semi-supervised fuzzy K-NN for cancer classification from microarray gene expression data

Semi-supervised fuzzy K-NN for cancer classification from mi...

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International Conference on Automation, Control, Energy and Systems (ACES)

作者： Anindya Halder Subhashis Misra Department Of Computer Application North-Eastern Hill University Tura Meghalaya India Department Of Computer Science Engineering Academy of Technology West Bengal India

Cancer classification from microarray gene expression data is a challenging task in computational biology and bioinformatics as the sufficient number of labeled samples (required to train the traditional classifiers) are very expensive and difficult to collect. Therefore, the predication accuracies of the classifiers trained with limited training samples are often very low. Although, the unlabeled samples are relatively inexpensive and readily available, traditional classifiers not generally utilize the distribution of those unlabeled samples. In this context, this article presents a novel `self-training' based semi-supervised classification method using fuzzy K-Nearest Neighbour algorithm which utilizes the unlabeled samples along with the labeled samples to improve the prediction accuracy of the cancer classification. The proposed method is evaluated with a number of microarray gene expression cancer data sets. Experimental results justify the potentiality of the proposed semi-supervised method for cancer classification using microarray gene expression data in comparison to its other supervised counterparts.

关键词： Gene expression Cancer Accuracy Tumors Support vector machines Training Prediction algorithms

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