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Gradual Identity Exposure Using Attribute-Based Encryption

Gradual Identity Exposure Using Attribute-Based Encryption

引用

IEEE International Conference on Social computing (SocialCom)

作者： Dijiang Huang Zhibin Zhou Zhu Yan School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe USA Computer Science Peking University Beijing China

Many Attribute-Based Encryption (ABE) schemes do not protect receivers' privacy, such that all the attributes to describe the eligible receivers are transmitted in plaintexts. Hidden policy-based ABE schemes have been proposed to protect receivers' privacy by using a construction that requires every user in the system to decrypt the ciphertext using all the attributes they possess, which incurs great computation and communication overhead. To address this issue, in this paper, we propose a new concept Gradual Identity Exposure (GIE) to protect data receivers' identity. Our approach is to reveal the receivers' information gradually by allowing ciphertext recipients for decrypting the message using their possessed attributes oneby-one (but not all). If the receiver does not possess one attribute in this procedure, the rest of attributes are still hidden. Compared to hidden-policy based solutions, GIE provides significant performance improvement in terms of reducing both computation and communication overhead. We also present a theoretical framework to model the GIE with several new proposed concepts.

关键词： Receivers Encryption Uncertainty Construction industry Privacy Polynomials

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SecureCloud: Towards a Comprehensive Security Framework for Cloud computing Environments

SecureCloud: Towards a Comprehensive Security Framework for ...

引用

IEEE Annual Computer Software and Applications Conference Workshops (COMPSACW)

作者： Hassan Takabi James B. D. Joshi Gail-Joon Ahn School of Information Sciences University of Pittsburgh Pittsburgh PA USA School of Computing Informatics and Decisions Systems Engineering Arizona State University Tempe AZ USA

Cloud computing has recently gained tremendous momentum but still is in its infancy. It has the potential for significant cost reduction and the increased operating efficiencies in computing. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this paper, we propose a comprehensive security framework for cloud computing environments. We also discuss challenges, existing solutions, approaches, and future work needed to provide a trustworthy cloud computing environment.

关键词： Clouds Access control Cloud computing Privacy Semantics Google

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Joint image fusion algorithm with OMP and wavelet

Joint image fusion algorithm with OMP and wavelet

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International Conference on Natural Computation (ICNC)

作者： Yi Sun Zhanwei Liu Qin Li School of Electric and Electronical Engineering North China Electric Power University Beijing 102206 China School of Computing and Informatics Shijiazhuang Railway Institute 050043 China

This paper presents a novel image fusion method based on orthogonal matching pursuit (OMP) and wavelet. Exploiting the OMP algorithm, the main nonlinear features of source images are extracted and fused together under the constraint of the approximation error. Then the residual images are continued to be fused through a wavelet fusion method. Experimental results demonstrate that the proposed algorithm can achieve better performance than the traditional wavelet method in combining and preserving important details in the composite images.

关键词： Matching pursuit algorithms Image fusion Dictionaries Approximation algorithms Wavelet transforms Measurement Algorithm design and analysis

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Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework

Kernel Learning for Efficiency Maximization in the Conformal...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Vineeth Balasubramanian Shayok Chakraborty Sethuraman Panchanathan Jieping Ye Center of Cognitive Ubiquitous Computing (CUbiC) Arizona State University Tempe AZ USA School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA

The Conformal Predictions framework is a recent development in machine learning to associate reliable measures of confidence with results in classification and regression. This framework is founded on the principles of algorithmic randomness (Kolmogorov complexity), transductive inference and hypothesis testing. While the formulation of the framework guarantees validity, the efficiency of the framework depends greatly on the choice of the classifier and appropriate kernel functions or parameters. While this framework has extensive potential to be useful in several applications, the lack of efficiency can limit its usability. In this paper, we propose a novel kernel learning methodology to maximize efficiency in the CP framework. This method is validated using the k-Nearest Neighbors classifier on three different datasets, and our results show immense promise in applying this method to obtain efficient conformal predictors that can be practically useful.

关键词： Kernel Machine learning Equations Support vector machines Prediction algorithms Zinc Testing

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A Multi-reality Approach to CRN Data Representation

A Multi-reality Approach to CRN Data Representation

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Alexandru Popescu David Erman Markus Fiedler Demetres Kouvatsos Department of Computing School of Informatics University of Bradford Bradford West Yorkshire UK Department of Telecommunication Systems School of Engineering Blekinge Institute of Technology Karlskrona Sweden

Cognitive Radio Networks (CRNs) are emerging as a viable solution for exploiting the available spectrum and solving overcrowding in the operating bands. Several dimensions in the process of identification, management and routing need to be handled to overcome the challenges associated with the management of CRNs. A very important topic in achieving an effective and flexible management solution is related to the data representation of the different CRN dimensions. Scalability, high tolerance to churn and low latencies in accessing the stored data are fundamental characteristics in order to keep up with the dynamic nature of a mobile environment. Accordingly, to achieve a robust data representation that can handle all these requirements in an efficient way we focus our attention on peer-to-peer (P2P) systems. These systems are well known for providing an efficient platform to develop scalable and robust applications. Hence, in this paper we investigate using geometric multi-dimensional data representation and addressing system based on basic CAN functionality. Results obtained in our experiments are reported, providing useful information to improve the resilience to churn of our system.

关键词： Peer to peer computing Routing Tin Fault tolerance Fault tolerant systems Computer architecture Computational modeling

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An Approach for Protecting Privacy on Social Networks

An Approach for Protecting Privacy on Social Networks

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International Conference on Systems and Networks Communications (ICSNC)

作者： Asim Sinan Yüksel Mehmet Erkan Yuksel Abdul Halim Zaim Computer Science Department School Of Informatics and Computing Indiana University Bloomington Indiana USA Computer Engineering Department Istanbul University Istanbul Turkey

Social networking has become a part of our life. We redundantly share our personal information with people in social networks and Internet. These networks allow users to share just about everything: data, photos, videos, favorite music, status updates, and more applications. Sharing large amounts of information causes privacy and security problems for users in these networks. To prevent privacy problems, we can provide built-in applications that help to protect our privacy by limiting the friends who get access to our personal information. Many users still do not make use of these applications. Users fail to use the application either because they are not aware that it exists or because of the tedious process that is involved when manually grouping friends into different categories to form a friends list. The privacy problem has prompted us to provide a solution that offers the social networks users an opportunity to protect their privacy. In this study, a privacy and security technique, its algorithm and design were mentioned. Our approach proposes an API, which provides grouping of friends through an automated system into different social groups by analyzing the user's social graph and depending on what common information they would like to share that should not be accessed by other friends. We assume that a user shares the same information in a group, as we call social circles. Finding these social circles will help users to group their friends easily and meaningfully.

关键词： Privacy Facebook Clustering algorithms Internet Security Visualization

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Can we evaluate the quality of software engineering experiments? 10

Can we evaluate the quality of software engineering experime...

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Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software engineering and Measurement

作者： Kitchenham, Barbara Sjøberg, Dag I. K. Brereton, O. Pearl Budgen, David Dybå, Tore Höst, Martin Pfahl, Dietmar Runeson, Per School of Computing and Mathematics Keele University Keele Staffordshire ST5 5BG United Kingdom Department of Informatics University of Oslo Blindern NO-0316 Oslo Norway School of Engineering and Computing Sciences Durham University Science Laboratories Durham DH1 3LE United Kingdom SINTEF Trondheim Norway Department of Computer Science Lund University SE-221 00 Lund Sweden University of Calgary Canada

ISBN: (纸本)9781450300391

Context: The authors wanted to assess whether the quality of published human-centric software engineering experiments was improving. This required a reliable means of assessing the quality of such experiments. Aims: The aims of the study were to confirm the usability of a quality evaluation checklist, determine how many reviewers were needed per paper that reports an experiment, and specify an appropriate process for evaluating quality. Method: With eight reviewers and four papers describing human-centric software engineering experiments, we used a quality checklist with nine questions. We conducted the study in two parts: the first was based on individual assessments and the second on collaborative evaluations. Results: The inter-rater reliability was poor for individual assessments but much better for joint evaluations. Four reviewers working in two pairs with discussion were more reliable than eight reviewers with no discussion. The sum of the nine criteria was more reliable than individual questions or a simple overall assessment. Conclusions: If quality evaluation is critical, more than two reviewers are required and a round of discussion is necessary. We advise using quality criteria and basing the final assessment on the sum of the aggregated criteria. The restricted number of papers used and the relatively extensive expertise of the reviewers limit our results. In addition, the results of the second part of the study could have been affected by removing a time restriction on the review as well as the consultation process. © 2010 ACM.

关键词： Quality control

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Robust quantum Kalman filtering under the phase uncertainty of the probe-laser

Robust quantum Kalman filtering under the phase uncertainty ...

引用

IEEE International Symposium on Computer-Aided Control System Design

作者： Iida, Sanae Ohki, Kentaro Yamamoto, Naoki Department of Applied Physics and Physico-Informatics Keio University 3-14-1 Hiyoshi Kouhoku Yokohama 223-8522 Japan Department of Information Physics and Computing Graduate School of Information Science and Engineering University of Tokyo 7-3-1 Hongo Bunkyo-Ku Tokyo 113-8656 Japan

ISBN: (纸本)9781424453542

The quantum Kalman filter has enough specification for accurate estimation and control in linear quantum systems, though this holds only in the case when the system parameters are completely known as in the classical case. In this paper, we consider an optical system containing an uncertain parameter in the probe-laser and propose a robust filtering scheme against this uncertainty. The filter estimates the uncertain parameter using an additional hardware probe sensor and adaptively changes the filtering algorithm so that it acquires the better estimation performance near to that of the optimal true filter. The robustness is explicitly evaluated in terms of the estimation error and is also numerically demonstrated. © 2010 IEEE.

关键词： Kalman filters

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Efficient Common Items Extraction from Multiple Sorted Lists

Efficient Common Items Extraction from Multiple Sorted Lists

引用

International Asia-Pacific Web Conference (APWEB)

作者： Wei Lu Chuitian Rong Jinchuan Chen Xiaoyong Du Gabriel Pui Cheong Fung Xiaofang Zhou Ministry of Education Key Laboratories of Data Engineering and Knowledge Engineering China School of Information Renmin University of China China School of Computing Informatics Arizona State University USA School of ITEE University of Queensland Australia

Given a set of lists, where items of each list are sorted by the ascending order of their values, the objective of this paper is to figure out the common items that appear in all of the lists efficiently. This problem is sometimes known as common items extraction from sorted lists. To solve this problem, one common approach is to scan all items of all lists sequentially in parallel until one of the lists is exhausted. However, we observe that if the overlap of items across all lists is not high, such sequential access approach can be significantly improved. In this paper, we propose two algorithms, MergeSkip and MergeESkip, to solve this problem by taking the idea of skipping as many items of lists as possible. As a result, a large number of comparisons among items can be saved, and hence the efficiency can be improved. We conduct extensive analysis of our proposed algorithms on one real dataset and two synthetic datasets with different data distributions. We report all our findings in this paper.

关键词： Data mining Data engineering Knowledge engineering informatics Algorithm design and analysis Computer science Application software Information retrieval

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Semantization Improves the Energy Efficiency of Wireless Sensor Networks

Semantization Improves the Energy Efficiency of Wireless Sen...

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IEEE Conference on Wireless Communications and Networking

作者： Peng Liu Y. Fun Hu Geyong Min Guojun Dai School of Engineering Design and Technology University of Bradford UK Institute of Computer Application Technology Hangzhou Dianzi University China School of Computing Informatics and Media University of Bradford UK

Wireless sensor networks(WSNs) have been increasingly available for large-scale applications in which energy efficiency is an important performance measure. These applications include environmental monitoring and structure monitoring which demand multifarious data. Driven by the energy limitation nature of WSNs lots of research works have been done in aspects such as nodes deployment, routing protocol, topology control, data reduction, sleep scheduling, etc. However, heterogeneous, i.e. hybrid sensor nodes are combined together into semantic sensor networks to provide large-scale applications with content rich information. In this paper, we discuss the potential of energy efficiency that semantization could bring to sensor networks. First we have an overview of some related work and then address current approaches of energy conservation in WSNs as well as how semantization can contribute in each aspect of saving energy. Finally a recommendatory architecture of semantic sensor network is proposed. Semantization will be a promising solution to improve energy efficiency together with system performance.

关键词： Energy efficiency Wireless sensor networks Large-scale systems Monitoring Energy measurement Routing protocols Network topology Sleep Potential energy Energy conservation

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