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International Workshop on Wireless Network Algorithm and Theory

作者： Zhang, Lei Wu, Qianhong Domingo-Ferrer, Josep Qin, Bo UNESCO in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Spain Wuhan University School of Computer Key Lab. of Aerospace Information Security and Trusted Computing China Xi'an University of Technology School of Science Department of Maths China

ISBN: (纸本)9780769543222

Certificateless cryptography eliminates the key escrow problem in identity-based cryptography. Hierarchical cryptography exploits a practical security model to mirror the organizational hierarchy in the real world. In this paper, to incorporate the advantages of both types of cryptosystems, we instantiate hierarchical certificateless cryptography by formalizing the notion of hierarchical certificateless signatures. Furthermore, we propose an HCLS scheme which, under the hardness of the computational Diffie-Hellman (CDH) problem, is proven to be existentially unforgeable against adaptive chosen-message attacks in the random oracle model. As to efficiency, our scheme has constant complexity, regardless of the depth of the hierarchy. Hence, the proposal is secure and scalable for practical applications. © 2010 IEEE.

关键词： Network security

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Proximity user identification using correlogram

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作者： Shahidi, Shervin Mazrooei, Parisa Esfahani, Navid Nasr Saraee, Mohammad Intelligent Databases Data Mining and Bioinformatics Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156-83111 Iran Isfahan Mathematics House Isfahan 81645-356 Iran School of Computing Science and Engineering University of Salford Greater Manchester United Kingdom

ISBN: (纸本)3642163262

This paper represents a technique, applying user action patterns in order to distinguish between users and identify them. In this method, users' actions sequences are mapped to numerical sequences and each user's profile is generated using autocorrelation values. Next, cross-correlation is used to compare user profiles with a test data. To evaluate our proposed method, a dataset known as Greenberg's dataset is used. The presented approach is succeeded to detect the correct user with as high as 82.3% accuracy over a set of 52 users. In comparison to the existing methods based on Hidden Markov Model or Neural Networks, our method needs less computation time and space. In addition, it has the ability of getting updated iteratively which is a main factor to facilitate transferability. © 2010 IFIP.

关键词： Pattern recognition

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Efficient Common Items Extraction from Multiple Sorted Lists

Efficient Common Items Extraction from Multiple Sorted Lists

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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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Hierarchical Certificateless Signatures

Hierarchical Certificateless Signatures

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IEEE/IFIP International Conference on Embedded and Ubiquitous computing, EUC

作者： Lei Zhang Qianhong Wu Josep Domingo-Ferrer Bo Qin UNESCO Chair in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Catalonia Spain School of Computer Key Laboratory of AeroSpace Information Security and Trusted Computing Wuhan University of Technology China School of Science Department of Maths Xi'an University of Technology China

Certificateless cryptography eliminates the key escrow problem in identity-based cryptography. Hierarchical cryptography exploits a practical security model to mirror the organizational hierarchy in the real world. In this paper, to incorporate the advantages of both types of cryptosystems, we instantiate hierarchical certificate less cryptography by formalizing the notion of hierarchical certificate less signatures. Furthermore, we propose an HCLS scheme which, under the hardness of the computational Diffie-Hellman (CDH) problem, is proven to be existentially unforgeable against adaptive chosen-message attacks in the random oracle model. As to efficiency, our scheme has constant complexity, regardless of the depth of the hierarchy. Hence, the proposal is secure and scalable for practical applications.

关键词： Public key Games Artificial intelligence Tin Protocols

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Approximation algorithm for constructing data aggregation trees for wireless sensor networks

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中国高等学校学术文摘·计算机科学 2009年第4期3卷 524-534页

作者： Deying LI Jiannong CAO Qinghua ZHU Key Laboratory of Data Engineering and Knowledge Engineering School of InformationRenmin University of ChinaBeijing 100872China Internet and Mobile Computing Lab Department of ComputingHong Kong Polytechnic UniversityHong KongChina

This paper considers the problem of constructing data aggregation trees in wireless sensor networks (WSNs)for a group of sensor nodes to send collected information to a single sink *** data aggregation tree contains the sink node,all the source nodes,and some other non-source *** goal of constructing such a data aggregation tree is to minimize the number of non-source nodes to be included in the tree so as to save *** prove that the data aggregation tree problem is NP-hard and then propose an approximation algorithm with a performance ratio of four and a greedy *** also give a distributed version of the approximation *** simulations are performed to study the performance of the proposed *** results show that the proposed algorithms can find a tree of a good approximation to the optimal tree and has a high degree of scalability.

关键词： WSNs data aggregation tree approximation algorithm distributed algorithm

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Measurement of Separate Cosmic-Ray Electron and Positron Spectra with the Fermi Large Area Telescope

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Physical Review Letters 2012年第1期108卷 011103-011103页

作者： M. Ackermann M. Ajello A. Allafort W. B. Atwood L. Baldini G. Barbiellini D. Bastieri K. Bechtol R. Bellazzini B. Berenji R. D. Blandford E. D. Bloom E. Bonamente A. W. Borgland A. Bouvier J. Bregeon M. Brigida P. Bruel R. Buehler S. Buson G. A. Caliandro R. A. Cameron P. A. Caraveo J. M. Casandjian C. Cecchi E. Charles A. Chekhtman C. C. Cheung J. Chiang S. Ciprini R. Claus J. Cohen-Tanugi J. Conrad S. Cutini A. de Angelis F. de Palma C. D. Dermer S. W. Digel E. do Couto e Silva P. S. Drell A. Drlica-Wagner C. Favuzzi S. J. Fegan E. C. Ferrara W. B. Focke P. Fortin Y. Fukazawa S. Funk P. Fusco F. Gargano D. Gasparrini S. Germani N. Giglietto P. Giommi F. Giordano M. Giroletti T. Glanzman G. Godfrey I. A. Grenier J. E. Grove S. Guiriec M. Gustafsson D. Hadasch A. K. Harding M. Hayashida R. E. Hughes G. Jóhannesson A. S. Johnson T. Kamae H. Katagiri J. Kataoka J. Knödlseder M. Kuss J. Lande L. Latronico M. Lemoine-Goumard M. Llena Garde F. Longo F. Loparco M. N. Lovellette P. Lubrano G. M. Madejski M. N. Mazziotta J. E. McEnery P. F. Michelson W. Mitthumsiri T. Mizuno A. A. Moiseev C. Monte M. E. Monzani A. Morselli I. V. Moskalenko S. Murgia T. Nakamori P. L. Nolan J. P. Norris E. Nuss M. Ohno T. Ohsugi A. Okumura N. Omodei E. Orlando J. F. Ormes M. Ozaki D. Paneque D. Parent M. Pesce-Rollins M. Pierbattista F. Piron G. Pivato T. A. Porter S. Rainò R. Rando M. Razzano S. Razzaque A. Reimer O. Reimer T. Reposeur S. Ritz R. W. Romani M. Roth H. F.-W. Sadrozinski C. Sbarra T. L. Schalk C. Sgrò E. J. Siskind G. Spandre P. Spinelli A. W. Strong H. Takahashi T. Takahashi T. Tanaka J. G. Thayer J. B. Thayer L. Tibaldo M. Tinivella D. F. Torres G. Tosti E. Troja Y. Uchiyama T. L. Usher J. Vandenbroucke V. Vasileiou G. Vianello V. Vitale A. P. Waite B. L. Winer K. S. Wood M. Wood Z. Yang S. Zimmer Deutsches Elektronen Synchrotron DESY D-15738 Zeuthen Germany W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics and SLAC National Accelerator Laboratory Stanford University Stanford California 94305 USA Santa Cruz Institute for Particle Physics Department of Physics and Department of Astronomy and Astrophysics University of California at Santa Cruz Santa Cruz California 95064 USA Istituto Nazionale di Fisica Nucleare Sezione di Pisa I-56127 Pisa Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste I-34127 Trieste Italy Dipartimento di Fisica Università di Trieste I-34127 Trieste Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova I-35131 Padova Italy Dipartimento di Fisica “G. Galilei” Università di Padova I-35131 Padova Italy Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Dipartimento di Fisica Università degli Studi di Perugia I-06123 Perugia Italy Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari 70126 Bari Italy Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 Palaiseau France Institut de Ciències de l’Espai (IEEE-CSIC) Campus UAB 08193 Barcelona Spain INAF-Istituto di Astrofisica Spaziale e Fisica Cosmica I-20133 Milano Italy Laboratoire AIM CEA-IRFU/CNRS/Université Paris Diderot Service d’Astrophysique CEA Saclay 91191 Gif sur Yvette France Artep Inc. 2922 Excelsior Springs Court Ellicott City Maryland 21042 USA National Research Council Research Associate National Academy of Sciences Washington D.C. 20001 USA ASI Science Data Center I-00044 Frascati (Roma) Italy Laboratoire Univers et Particules de Montpellier Université Montpellier 2 CNRS/IN2P3 Montpellier France Department of Physics Stockholm University AlbaNova SE-106 91 Stockholm Sweden The Oskar Klein Centre for Cosmoparticle Physics AlbaNova SE-1

We measured separate cosmic-ray electron and positron spectra with the Fermi Large Area Telescope. Because the instrument does not have an onboard magnet, we distinguish the two species by exploiting Earth’s shadow, which is offset in opposite directions for opposite charges due to Earth’s magnetic field. We estimate and subtract the cosmic-ray proton background using two different methods that produce consistent results. We report the electron-only spectrum, the positron-only spectrum, and the positron fraction between 20 and 200 GeV. We confirm that the fraction rises with energy in the 20–100 GeV range. The three new spectral points between 100 and 200 GeV are consistent with a fraction that is continuing to rise with energy.

关键词： COSMIC rays NUCLEAR physics COSMIC ray neutrons MAGNETIC fields PROTONS

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Reports of the AAAI 2010 conference workshops

Reports of the AAAI 2010 conference workshops

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作者： Aha, David W. Boddy, Mark Bulitko, Vadim D'Avila Garcez, Artur S. Doshi, Prashant Edelkamp, Stefan Geib, Christopher Gmytrasiewicz, Piotr Goldman, Robert P. Halevy, Alon Hitzler, Pascal Isbell, Charles Josyula, Darsana Kaelbling, Leslie Pack Kersting, Kristian Kunda, Maithilee Lamb, Luis C. Marthi, Bhaskara McGreggor, Keith Mihalkova, Lilyana Nastase, Vivi Natarajan, Sriraam Provan, Gregory Raja, Anita Ram, Ashwin Riedl, Mark Russell, Stuart Sabharwal, Ashish Smaus, Jan-Georg Sukthankar, Gita Tuyls, Karl Van Der Meyden, Ron Adaptive Systems Section Naval Research Laboratory Washington DC United States Adventium Labs. Minneapolis MN United States Department of Computer Science University of Alberta Canada City University London United Kingdom University of Georgia United States University of Bremen Germany School of Informatics University of Edinburgh United Kingdom University of Illinois Chicago United States Smart Information Flow Technologies LLC Minneapolis MN United States Structured Data Group Google Research United States Department of Computer Science Wright State University Dayton OH United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer Science Bowie State University United States Department of Computer Science and Engineering Massachusetts Institute of Technology United States Statistical Relational Mining Group Fraunhofer IAIS Germany Department of Computer Science Federal University of Rio Grande Do sul Brazil Willow Garage Inc. CA United States Computer Science Department University of Maryland College Park United States Heidelberg Institute for Theoretical Studies Heidelberg Germany Department of Computer Science University of Wisconsin Madison United States University College Cork Ireland Cork Complex Systems Lab. Ireland Department of Software and Information Systems University of North Carolina Charlotte United States Department of Computer Science and Engineering University of California Berkeley United States Department of Computer Science Cornell University United States Institute for Computational Sustainability United States University of Freiburg Germany School of Electrical Engineering and Computer Science University of Central Florida United States Maastricht University Netherlands University of New South Wales NICTA Australia

The AAAI-10 workshop program was held on July 11-12, 2010, at the Westin Peachtree Plaza in Atlanta, Georgia. The workshop program included 13 workshops covering a wide range of topics in artificial intelligence. There were several presentations on particular formalisms for combining the levels of planning from the perspectives of classical planning, motion planning, POMDPs, search-based planning, and temporal logic-based constraints. Henry Lieberman from Massachusetts Institute of Technology Media Laboratory presented work developing a platform for knowledge acquisition and usage from expert users, built upon experience with eliciting information from nonexperts in a collaborative manner. The objective of the AAAI Workshop on Goal-Directed Autonomy (GDA) was to encourage discussion and novel contributions on intelligent agents that can self-select their goals. Jeremy Baxter from QinetiQ focused on user interaction, while Nick Hawes described a goal-directed reasoning framework for controlling a mobile robot.

关键词： Motion planning

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TCD-DCU at log CLEF 2009: An analysis of queries, actions, and interface languages

TCD-DCU at log CLEF 2009: An analysis of queries, actions, a...

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2009 Cross Language Evaluation Forum Workshop, CLEF 2009, co-located with the 13th European Conference on Digital Libraries, ECDL 2009

作者： Ghorab, M. Rami Leveling, Johannes Zhou, Dong Jones, Gareth J. F. Wade, Vincent Centre for Next Generation Localisation Knowledge and Data Engineering Group Trinity College Dublin I-Dublin 2 Ireland Centre for Next Generation Localisation School of Computing Dublin City University I-Dublin 9 Ireland

This paper describes the collaborative participation of Trinity College Dublin and Dublin City University in the Log Analysis for Digital Societies (LADS) task of LogCLEF 2009 track. An analysis of multilingual search logs was carried out with the objectives of investigating how users from different linguistic or cultural backgrounds behave in search, and how the discovery of patterns in user actions could be used for community identification. Our findings suggest that there is scope for further investigation of how search logs can be exploited to personalise and improve cross-language search as well as improve the TEL search system.

关键词： Digital libraries

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Efficient mining of distance-based subspace clusters

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Statistical Analysis and data Mining 2009年第5-6期2卷 427-444页

作者： Liu, Guimei Sim, Kelvin Li, Jinyan Wong, Limsoon School of Computing National University of Singapore Singapore Data Mining Department Institute for Infocomm Research Singapore School of Computer Engineering Nanyang Technological University Singapore

Traditional similarity measurements often become meaningless when dimensions of datasets increase. Subspace clustering has been proposed to find clusters embedded in subspaces of high-dimensional datasets. Many existing algorithms use a grid-based approach to partition the data space into nonoverlapping rectangle cells, and then identify connected dense cells as clusters. The rigid boundaries of the grid-based approach may cause a real cluster to be divided into several small clusters. In this paper, we propose to use a sliding-window approach to partition the dimensions to preserve significant clusters. We call this model nCluster model. The sliding-window approach generates more bins than the grid-based approach, thus it incurs higher mining cost. We develop a deterministic algorithm, called MaxnCluster, to mine nClusters efficiently. MaxnCluster uses several techniques to speed up the mining, and it produces only maximal nClusters to reduce result size. Non-maximal nClusters are pruned without the need of storing the discovered nClusters in the memory, which is key to the efficiency of MaxnCluster. Our experiment results show that (i) the nCluster model can indeed preserve clusters that are shattered by the grid-based approach on synthetic datasets;(ii) the nCluster model produces more significant clusters than the grid-based approach on two real gene expression datasets and (iii) MaxnCluster is efficient in mining maximal nClusters. © 2009 Wiley Periodicals, Inc.

关键词： Clustering algorithms

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Web Service Integration for Next Generation Localisation

Web Service Integration for Next Generation Localisation

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2009 Workshop on Software engineering, Testing, and Quality Assurance for Natural Language Processing, SETQA-NLP 2009

作者： Lewis, David Curran, Stephen Feeney, Kevin Etzioni, Zohar Keeney, John Way, Andy Schäler, Reinhard Centre for Next Generation Localisation Knowledge and Data Engineering Group Trinity College Dublin Ireland Centre for Next Generation Localisation School of Computing Dublin City Universit Y Ireland Centre for Next Generation Localisation Centre for Localisation Research University of Limerick Ireland

ISBN: (纸本)9781932432329

Developments in Natural Language Processing technologies promise a variety of benefits to the localization industry, both in its current form in performing bulk enterprise-based localization and in the future in supporting personalized web-based localization on increasingly user-generated content. As an increasing variety of natural language processing services become available, it is vital that the localization industry employs the flexible software integration techniques that will enable it to make best use of these technologies. To date however, the localization industry has been slow reap the benefits of modern integration technologies such as web service integration and orchestration. Based on recent integration experiences, we examine how the localization industry can best exploit web-based integration technologies in developing new services and exploring new business models. © 2009 Association for Computational Linguistics.

关键词： Web services

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