Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIII: Selected Papers from FDSE 2014 PDF
Preview Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIII: Selected Papers from FDSE 2014
Tran Khanh Dang · Nam Thoai e n Guest Editors i l b u S l a Transactions on n r u o J Large-Scale 0 8 Data- and Knowledge- 4 9 S C Centered Systems XXIII N L Abdelkader Hameurlain • Josef Küng • Roland Wagner Editors-in-Chief Selected Papers from FDSE 2014 123 Lecture Notes in Computer Science 9480 Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison Lancaster University, Lancaster, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Zürich, Switzerland John C. Mitchell Stanford University, Stanford, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Dortmund, Germany Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbrücken, Germany More information about this series at http://www.springer.com/series/8637 ü Abdelkader Hameurlain Josef K ng (cid:129) Roland Wagner Tran Khanh Dang (cid:129) Nam Thoai (Eds.) Transactions on Large-Scale Data- and Knowledge- Centered Systems XXIII Selected Papers from FDSE 2014 123 Editors-in-Chief Abdelkader Hameurlain RolandWagner IRIT,PaulSabatier University FAW,University ofLinz Toulouse Linz France Austria Josef Küng FAW,University ofLinz Linz Austria GuestEditors Tran KhanhDang NamThoai HoChiMinhCityUniversityofTechnology HoChiMinhCityUniversityofTechnology HoChiMinh City HoChiMinh City Vietnam Vietnam ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notesin Computer Science ISBN 978-3-662-49174-4 ISBN978-3-662-49175-1 (eBook) DOI 10.1007/978-3-662-49175-1 LibraryofCongressControlNumber:2015958557 ©Springer-VerlagBerlinHeidelberg2016 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartofthe material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodologynow knownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbookare believedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsortheeditors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissionsthatmayhavebeenmade. Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringer-VerlagGmbHBerlinHeidelberg Preface The First International Conference on Future Data and Security Engineering (FDSE) washeldinHoChiMinhCity,Vietnam, November19–21,2014.FDSEistobecome an annual international forum designed for researchers and practitioners interested in state-of-the-artandstate-of-the-practiceactivitiesindata,information,knowledge,and securityengineeringtoexplorecutting-edgeideas,presentandexchangetheirresearch results andadvanceddata-intensiveapplications,aswell astodiscuss emerging issues ondata,information,knowledge,andsecurity engineering.Weinvitedthesubmission of both original research contributions and industry papers. At the annual FDSE, researchers and practitioners will not only be able to share research solutions to problemsoftoday’sdataandsecurityengineeringsociety,butalsoidentifynewissues and directions for future related research and development work. FDSE 2014 received 66 submissions and, after a careful review process, only 23 paperswereselectedforpresentation.Amongthosegreatpapers,weselectedonlyfive papers to invite the authors to revise, extend, and resubmit for publication in this special issue. The main focus of this special issue is on advanced computing issues in information and security engineering as well as their promising applications. The great success of FDSE 2014 as well as this special issue of TLDKS was the result of the efforts of many people, to whom we would like to express our gratitude. First, we would like to thank all authors who extended and submitted papers to this specialissue.Wewouldalsoliketothankthemembersofthecommitteesandexternal reviewers for their timely reviewing and lively participation in the subsequent dis- cussion in order to select such high-quality papers published in this issue. Finally yet importantly,wethankGabrielaWagnerforherenthusiastichelpandsupportduringthe whole process of preparation for this publication. September 2015 Tran Khanh Dang Nam Thoai Organization Editorial Board Reza Akbarinia Inria, France Bernd Amann LIP6 - UPMC, France Dagmar Auer FAW, Austria Stéphane Bressan National University of Singapore, Singapore Francesco Buccafurri Università Mediterranea di Reggio Calabria, Italy Qiming Chen HP-Lab, USA Tommaso Di Noia Politecnico di Bari, Italy Dirk Draheim University of Innsbruck, Austria Johann Eder Alpen Adria University Klagenfurt, Austria Stefan Fenz Vienna University of Technology, Austria Georg Gottlob Oxford University, UK Anastasios Gounaris Aristotle University of Thessaloniki, Greece Theo Härder Technical University of Kaiserslautern, Germany Andreas Herzig IRIT, Paul Sabatier University, France Hilda Kosorus FAW, Austria Dieter Kranzlmüller Ludwig-Maximilians-Universität München, Germany Philippe Lamarre INSA Lyon, France Lenka Lhotská Technical University of Prague, Czech Republic Vladimir Marik Technical University of Prague, Czech Republic Mukesh Mohania IBM India, India Franck Morvan Paul Sabatier University, IRIT, France Kjetil Nørvåg Norwegian University of Science and Technology, Norway Gultekin Ozsoyoglu Case Western Reserve University, USA Themis Palpanas Paris Descartes University, France Torben Bach Pedersen Aalborg University, Denmark Günther Pernul University of Regensburg, Germany Klaus-Dieter Schewe University of Linz, Austria David Taniar Monash University, Australia A. Min Tjoa Vienna University of Technology, Austria Chao Wang Oak Ridge National Laboratory, USA Reviewers Lam Son Le HCMCUniversityofTechnology,VietnamandUniversity of Wollongong, Australia Thanh Binh Nguyen HCMC University of Technology, Vietnam VIII Organization Minh-Quang Tran HCMC University of Technology, Vietnam and National Institute of Informatics, Japan Hoang Tam Vo SAP and National University of Singapore, Singapore Nguyen Ngoc Thien An University College Dublin, Ireland Viet-Hung Nguyen University of Trento, Italy Phan Trong Nhan Johannes Kepler University Linz, Austria Quoc Cuong To INRIA Rocquencourt, Versailles, France Le Thi Kim Tuyen Sungkyunkwan University, South Korea Tran Tri Dang HCMC University of Technology, Vietnam Contents A Natural Language Processing Tool for White Collar Crime Investigation . . . 1 Maarten van Banerveld, Mohand-Tahar Kechadi, and Nhien-An Le-Khac DataLeakageAnalysisoftheHibernateQueryLanguageonaPropositional Formulae Domain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Raju Halder, Angshuman Jana, and Agostino Cortesi An Adaptive Similarity Search in Massive Datasets. . . . . . . . . . . . . . . . . . . 45 Trong Nhan Phan, Josef Küng, and Tran Khanh Dang Semantic Attack on Anonymised Transactions . . . . . . . . . . . . . . . . . . . . . . 75 Jianhua Shao and Hoang Ong Private Indexes for Mixed Encrypted Databases . . . . . . . . . . . . . . . . . . . . . 100 Yi Tang, Xiaolei Zhang, and Ji Zhang Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 A Natural Language Processing Tool for White Collar Crime Investigation Maarten van Banerveld2, Mohand-Tahar Kechadi1, and Nhien-An Le-Khac1(&) 1 Schoolof Computer Science andInformatics, University CollegeDublin, Belfield,Dublin4, Ireland {tahar.kechadi,an.lekhac}@ucd.ie 2 Surinameweg, 42035VAHaarlem, TheNetherlands [email protected] Abstract. In today’s world we are confronted with increasing amounts of information every day coming from a large variety of sources. People and corporations are producing data on a large scale, and since the rise of the internet, e-mail and social media the amount of produced data has grown exponentially.Fromalawenforcementperspectivewehavetodealwiththese huge amounts of data when a criminal investigation is launched against an individual or company. Relevant questions need to be answered like who committed the crime, who were involved, what happened and on what time, who were communicating and about what? Not only the amount of available data to investigate has increased enormously, but also the complexity of this data has increased. When these communication patterns need to be combined withforinstanceaseizedfinancialadministrationorcorporatedocumentshares acomplexinvestigation problemarises.Recently, criminalinvestigators facea huge challenge when evidence of a crime needs to be found in the Big Data environmentwheretheyhavetodealwithlargeandcomplexdatasetsespecially in financial and fraud investigations. To tackle this problem, a financial and fraudinvestigationunitofaEuropeancountryhasdevelopedanewtoolnamed LESthatusesNaturalLanguageProcessing(NLP)techniquestohelpcriminal investigatorshandlelargeamountsoftextualinformationinamoreefficientand fasterway.Inthispaper,wepresentthistoolandwefocusontheevaluationits performance in terms of the requirements of forensic investigation: speed, smarter and easier for investigators. In orderto evaluate this LEStool, we use different performance metrics. We also show experimental results of our eval- uation with large andcomplex datasets from real-worldapplication. (cid:1) (cid:1) Keywords: Big data Natural language processing Financial and fraud (cid:1) investigation Hadoop/MapReduce 1 Introduction Since the start of the digital information age to the rise of the Internet, the amount of digital data has dramatically increased. Indeed, we are dealing with many challenges when it comes to data. Some data is structured and stored in a traditional relational ©Springer-VerlagBerlinHeidelberg2016 A.Hameurlainetal.(Eds.):TLDKSXXIII,LNCS9480,pp.1–22,2016. DOI:10.1007/978-3-662-49175-1_1
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