This book focuses on the modeling and management of spatial data in distributed systems. The authors have structured the contributions from internationally renowned researchers into four parts. The book offers researchers an excellent overview of the state-of-the-art in modeling and management of spatial data in distributed environments, while it may also be the basis of specialized courses on Web-based geographical information systems.

ThisvolumecontainstheproceedingsofIFIPTM2009, theThirdIFIPWG11.11 International Conference on Trust Management, held at Purdue University in West Lafayette, Indiana, USA during June 15-19, 2009. IFIPTM 2009 provided a truly global platform for the reporting of research, development, policyandpracticeintheinterdependentareasofprivacy, security, and trust. Building on the traditions inherited from the highly successful iTrust conference series, the IFIPTM 2007 conference in Moncton, New Brunswick, Canada, and the IFIPTM 2008conferencein Trondheim, Norway, IFIPTM 2009 focusedontrust, privacyand security from multidisciplinary perspectives. The conferenceisanarenafor discussionaboutrelevantproblemsfromboth research and practice in the areas of academia, business, and government. IFIPTM 2009 was an open IFIP conference. The program of the conference featured both theoretical research papers and reports of real-world case studies. IFIPTM 2009 received 44 submissions. The ProgramCommittee selected 17 - pers for presentation and inclusion in the proceedings. In addition, the program and the proceedings include one invited paper and ?ve demo descriptions. The highlights of IFIPTM 2009 included invited talks and tutorials by academic and governmental experts in the ?elds of trust management, privacy and security, including Eugene Spa?ord, Marianne Winslett, and Michael Novak. Running an international conference requires an immense e?ort from all p- ties involved. We would like to thank the Program Committee members and external referees for having provided timely and in-depth reviews of the subm- ted papers.We wouldalsolike to thank the Workshop, Tutorial, Demonstration, Local Arrangements, and Website Chairs, for having provided great help or- nizing the con

Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover well-established results-they also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development. Divided into seven parts, the book provides in-depth coverage of the most novel reference scenarios for privacy-preserving techniques. The first part gives general techniques that can be applied to various applications discussed in the rest of the book. The second section focuses on the sanitization of network traces and privacy in data stream mining. After the third part on privacy in spatio-temporal data mining and mobility data analysis, the book examines time series analysis in the fourth section, explaining how a perturbation method and a segment-based method can tackle privacy issues of time series data. The fifth section on biomedical data addresses genomic data as well as the problem of privacy-aware information sharing of health data. In the sixth section on web applications, the book deals with query log mining and web recommender systems. The final part on social networks analyzes privacy issues related to the management of social network data under different perspectives. While several new results have recently occurred in the privacy, database, and data mining research communities, a uniform presentation of up-to-date techniques and applications is lacking. Filling this void, Privacy-Aware Knowledge Discovery presents novel algorithms, patterns, and models, along with a significant collection of open problems for future investigation.

Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover well-established results -- they also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development. Divided into seven parts, the book provides in-depth coverage of the most novel reference scenarios for privacy-preserving techniques. The first part gives general techniques that can be applied to various applications discussed in the rest of the book. The second section focuses on the sanitization of network traces and privacy in data stream mining. After the third part on privacy in spatio-temporal data mining and mobility data analysis, the book examines time series analysis in the fourth section, explaining how a perturbation method and a segment-based method can tackle privacy issues of time series data. The fifth section on biomedical data addresses genomic data as well as the problem of privacy-aware information sharing of health data. In the sixth section on web applications, the book deals with query log mining and web recommender systems. The final part on social networks analyzes privacy issues related to the management of social network data under different perspectives. While several new results have recently occurred in the privacy, database, and data mining research communities, a uniform presentation of up-to-date techniques and applications is lacking. Filling this void, Privacy-Aware Knowledge Discovery presents novel algorithms, patterns, and models, along with a significant collection of open problems for future investigation.

ThisvolumecontainstheproceedingsofIFIPTM2009, theThirdIFIPWG11.11 International Conference on Trust Management, held at Purdue University in West Lafayette, Indiana, USA during June 15-19, 2009. IFIPTM 2009 provided a truly global platform for the reporting of research, development, policyandpracticeintheinterdependentareasofprivacy, security, and trust. Building on the traditions inherited from the highly successful iTrust conference series, the IFIPTM 2007 conference in Moncton, New Brunswick, Canada, and the IFIPTM 2008conferencein Trondheim, Norway, IFIPTM 2009 focusedontrust, privacyand security from multidisciplinary perspectives. The conferenceisanarenafor discussionaboutrelevantproblemsfromboth research and practice in the areas of academia, business, and government. IFIPTM 2009 was an open IFIP conference. The program of the conference featured both theoretical research papers and reports of real-world case studies. IFIPTM 2009 received 44 submissions. The ProgramCommittee selected 17 - pers for presentation and inclusion in the proceedings. In addition, the program and the proceedings include one invited paper and ?ve demo descriptions. The highlights of IFIPTM 2009 included invited talks and tutorials by academic and governmental experts in the ?elds of trust management, privacy and security, including Eugene Spa?ord, Marianne Winslett, and Michael Novak. Running an international conference requires an immense e?ort from all p- ties involved. We would like to thank the Program Committee members and external referees for having provided timely and in-depth reviews of the subm- ted papers.We wouldalsolike to thank the Workshop, Tutorial, Demonstration, Local Arrangements, and Website Chairs, for having provided great help or- nizing the con

This book focuses on the modeling and management of spatial data in distributed systems. The authors have structured the contributions from internationally renowned researchers into four parts. The book offers researchers an excellent overview of the state-of-the-art in modeling and management of spatial data in distributed environments, while it may also be the basis of specialized courses on Web-based geographical information systems.

Access control is one of the fundamental services that any Data Management System should provide. Its main goal is to protect data from unauthorized read and write operations. This is particularly crucial in today's open and interconnected world, where each kind of information can be easily made available to a huge user population, and where a damage or misuse of data may have unpredictable consequences that go beyond the boundaries where data reside or have been generated. This book provides an overview of the various developments in access control for data management systems. Discretionary, mandatory, and role-based access control will be discussed, by surveying the most relevant proposals and analyzing the benefits and drawbacks of each paradigm in view of the requirements of different application domains. Access control mechanisms provided by commercial Data Management Systems are presented and discussed. Finally, the last part of the book is devoted to discussion of some of the most challenging and innovative research trends in the area of access control, such as those related to the Web 2.0 revolution or to the Database as a Service paradigm. This book is a valuable reference for an heterogeneous audience. It can be used as either an extended survey for people who are interested in access control or as a reference book for senior undergraduate or graduate courses in data security with a special focus on access control. It is also useful for technologists, researchers, managers, and developers who want to know more about access control and related emerging trends. Table of Contents: Access Control: Basic Concepts / Discretionary Access Control for Relational Data Management Systems / Discretionary Access Control for Advanced Data Models / Mandatory Access Control / Role-based Access Control / Emerging Trends in Access Control

This book constitutes the thoroughly refereed post-workshop proceedings of the Second International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2008, held in Las Vegas, NV, USA, in March 2008 in conjunction with the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008.

The 5 revised full papers presented together with 1 invited keynote lecture and 2 invited panel sessions were carefully reviewed and selected from numerous submissions. The papers are extended versions of the workshop presentations and incorporate reviewers' comments and discussions at the workshop and represent the diversity of data mining research issues in privacy, security, and trust as well as current work on privacy issues in geographic data mining.

Vast amounts of data are collected by service providers and system administ- tors, and are available in public information systems. Data mining technologies provide an ideal framework to assist in analyzing such collections for computer security and surveillance-related endeavors. For instance, system administrators can apply data mining to summarize activity patterns in access logs so that potential malicious incidents can be further investigated. Beyond computer - curity, data mining technology supports intelligence gathering and summari- tion for homeland security. For years, and most recently fueled by events such as September 11, 2001, government agencies have focused on developing and applying data mining technologies to monitor terrorist behaviors in public and private data collections. Theapplicationof data mining to person-speci?cdata raisesseriousconcerns regarding data con?dentiality and citizens' privacy rights. These concerns have led to the adoption of various legislation and policy controls. In 2005, the - ropean Union passed a data-retention directive that requires all telephone and Internetservice providersto store data ontheir consumers for up to two yearsto assist in the prevention of terrorismand organized crime. Similar data-retention regulationproposalsareunderheateddebateintheUnitedStatesCongress. Yet, the debate often focuses on ethical or policy aspects of the problem, such that resolutions have polarized consequences; e. g. , an organization can either share data for data mining purposes or it can not. Fortunately, computer scientists, and data mining researchers in particular, have recognized that technology can beconstructedtosupportlesspolarizedsolutions. Computerscientistsaredev- oping technologies that enable data mining goals without sacri?cing the privacy and security of the individuals to whom the data correspond.

The 9th International Conference on Extending Database Technology, EDBT 2004, was held in Heraklion, Crete, Greece, during March 14-18, 2004. The EDBT series of conferences is an established and prestigious forum for the exchange of the latest research results in data management. Held every two years in an attractive European location, the conference provides unique opp- tunities for database researchers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences. The previous events were held in Venice, Vienna, Cambridge, Avignon, Valencia, Konstanz, and Prague. EDBT 2004 had the theme "new challenges for database technology," with the goal of encouraging researchers to take a greater interest in the current exciting technological and application advancements and to devise and address new research and development directions for database technology. From its early days, database technology has been challenged and advanced by new uses and applications, and it continues to evolve along with application requirements and hardware advances. Today's DBMS technology faces yet several new challenges. Technological trends and new computation paradigms, and applications such as pervasive and ubiquitous computing, grid computing, bioinformatics, trust management, virtual communities, and digital asset management, to name just a few, require database technology to be deployed in a variety of environments and for a number of di?erent purposes. Such an extensive deployment will also require trustworthy, resilient database systems, as well as easy-to-manage and ?exible ones, to which we can entrust our data in whatever form they are.