The Complete Book of Data Anonymization

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization.

The Complete Book of Data Anonymization

Author: Balaji Raghunathan

Publisher: CRC Press

ISBN: 1439877300

Page: 267

View: 479

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a practitioner's and a program sponsor's perspective. Discussing analysis, planning, setup, and governance, it illustrates the entire process of adapting and implementing anonymization tools and programs. Part I of the book begins by explaining what data anonymization is. It describes how to scope a data anonymization program as well as the challenges involved when planning for this initiative at an enterprisewide level. Part II describes the different solution patterns and techniques available for data anonymization. It explains how to select a pattern and technique and provides a phased approach towards data anonymization for an application. A cutting-edge guide to data anonymization implementation, this book delves far beyond data anonymization techniques to supply you with the wide-ranging perspective required to ensure comprehensive protection against misuse of data.

Database Anonymization

If merging sensitive data from several sources, the incoming data may already have been anonymized at the source (in fact they probably should).

Database Anonymization

Author: Josep Domingo-Ferrer

Publisher: Morgan & Claypool Publishers

ISBN: 1627058443

Page: 136

View: 920

The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature. Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guarantees they offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer.

Database Anonymization

The current social and economic context increasingly demands open data to improve scientific research and decision making.

Database Anonymization

Author: Josep Domingo-Ferrer

Publisher: Morgan & Claypool Publishers

ISBN: 1681731983

Page: 136

View: 643

The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature. Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guarantees they offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer.

The Complete Book of Data Anonymization

Leveraging Data Anonymization Techniques Prerequisites When applied on a database, anonymization techniques must ensure that the: 1.

The Complete Book of Data Anonymization

Author: Balaji Raghunathan

Publisher: CRC Press

ISBN: 1439877319

Page: 267

View: 727

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a practitioner's and a program sponsor's perspective. Discussing analysis, planning, setup, and governance, it illustrates the entire process of adapting an

Anonymizing Health Data

Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity.

Anonymizing Health Data

Author: Khaled El Emam

Publisher: "O'Reilly Media, Inc."

ISBN: 1449363032

Page: 228

View: 145

Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets

Anonymization of Electronic Medical Records to Support Clinical Analysis

Academics and other research scientists will also find the book invaluable.

Anonymization of Electronic Medical Records to Support Clinical Analysis

Author: Aris Gkoulalas-Divanis

Publisher: Springer Science & Business Media

ISBN: 1461456673

Page: 72

View: 328

Anonymization of Electronic Medical Records to Support Clinical Analysis closely examines the privacy threats that may arise from medical data sharing, and surveys the state-of-the-art methods developed to safeguard data against these threats. To motivate the need for computational methods, the book first explores the main challenges facing the privacy-protection of medical data using the existing policies, practices and regulations. Then, it takes an in-depth look at the popular computational privacy-preserving methods that have been developed for demographic, clinical and genomic data sharing, and closely analyzes the privacy principles behind these methods, as well as the optimization and algorithmic strategies that they employ. Finally, through a series of in-depth case studies that highlight data from the US Census as well as the Vanderbilt University Medical Center, the book outlines a new, innovative class of privacy-preserving methods designed to ensure the integrity of transferred medical data for subsequent analysis, such as discovering or validating associations between clinical and genomic information. Anonymization of Electronic Medical Records to Support Clinical Analysis is intended for professionals as a reference guide for safeguarding the privacy and data integrity of sensitive medical records. Academics and other research scientists will also find the book invaluable.

Database Systems for Advanced Applications

Distributed Anonymization for Multiple Data Providers in a Cloud System Xiaofeng Ding1,2, Qing Yu2, Jiuyong Li1, Jixue Liu1, and Hai Jin2 1 School of ...

Database Systems for Advanced Applications

Author: Weiyi Meng

Publisher: Springer

ISBN: 3642374875

Page: 489

View: 669

This two volume set LNCS 7825 and LNCS 7826 constitutes the refereed proceedings of the 18th International Conference on Database Systems for Advanced Applications, DASFAA 2013, held in Wuhan, China, in April 2013. The 51 revised full papers and 10 short papers presented together with 2 invited keynote talks, 1 invited paper, 3 industrial papers, 9 demo presentations, 4 tutorials and 1 panel paper were carefully reviewed and selected from a total of 227 submissions. The topics covered in part 1 are social networks; query processing; nearest neighbor search; index; query analysis; XML data management; privacy protection; and uncertain data management; and in part 2: graph data management; physical design; knowledge management; temporal data management; social networks; query processing; data mining; applications; and database applications.

Anonymizing Health Data

The successful deployment of anonymization within an organization—whether it's ... the stakeholders believe that they actually need to anonymize their data.

Anonymizing Health Data

Author: Khaled El Emam

Publisher: "O'Reilly Media, Inc."

ISBN: 1449363059

Page: 228

View: 297

Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets

Handbook of Research on Computational Intelligence for Engineering Science and Business

In order to handle uncertainty in the database anonymization process, ... uncertainty while using t-closeness in the process of anonymization of databases.

Handbook of Research on Computational Intelligence for Engineering  Science  and Business

Author: Bhattacharyya, Siddhartha

Publisher: IGI Global

ISBN: 1466625198

Page: 746

View: 120

Using the same strategy for the needs of image processing and pattern recognition, scientists and researchers have turned to computational intelligence for better research throughputs and end results applied towards engineering, science, business and financial applications. Handbook of Research on Computational Intelligence for Engineering, Science, and Business discusses the computation intelligence approaches, initiatives and applications in the engineering, science and business fields. This reference aims to highlight computational intelligence as no longer limited to computing-related disciplines and can be applied to any effort which handles complex and meaningful information.

Database and Expert Systems Applications

Manual anonymization is however, a timeconsuming and error-prone procedure that can result in inadvertent disclosures of information.

Database and Expert Systems Applications

Author: Sven Hartmann

Publisher: Springer

ISBN: 3319444034

Page: 449

View: 544

This two volume set LNCS 9827 and LNCS 9828 constitutes the refereed proceedings of the 27th International Conference on Database and Expert Systems Applications, DEXA 2016, held in Porto, Portugal, September 2016. The 39 revised full papers presented together with 29 short papers were carefully reviewed and selected from 137 submissions. The papers discuss a range of topics including: Temporal, Spatial, and High Dimensional Databases; Data Mining; Authenticity, Privacy, Security, and Trust; Data Clustering; Distributed and Big Data Processing; Decision Support Systems, and Learning; Data Streams; Data Integration, and Interoperability; Semantic Web, and Data Semantics; Social Networks, and Network Analysis; Linked Data; Data Analysis; NoSQL, NewSQL; Multimedia Data; Personal Information Management; Semantic Web and Ontologies; Database and Information System Architectures; Query Answering and Optimization; Information Retrieval, and Keyword Search; Data Modelling, and Uncertainty.

Data Privacy Management Cryptocurrencies and Blockchain Technology

We carry out experiments on database anonymization. We expected that the additional constraints for k-anonymization of dynamic databases would entail a ...

Data Privacy Management  Cryptocurrencies and Blockchain Technology

Author: Joaquin Garcia-Alfaro

Publisher: Springer

ISBN: 3030003051

Page: 442

View: 266

This book constitutes the refereed conference proceedings of the 2nd International Workshop on Cryprocurrencies and Blockchain Technology, CBT 2018, and the 13thInternational Workshop on Data Privacy Management, DPM 2018, on conjunction with the 23nd European Symposium on Research in Computer Security, ESORICS 2018, held in Barcelona, Spain, in September 2018. From the CBT Workshop 7 full and 8 short papers out of 39 submissions are included. The selected papers cover aspects of identity management, smart contracts, soft- and hardforks, proof-of-works and proof of stake as well as on network layer aspects and the application of blockchain technology for secure connect event ticketing. The DPM Workshop received 36 submissions from which 11 full and 5 short papers were selected for presentation. The papers focus on challenging problems such as translation of high-level buiness goals into system level privacy policies, administration of sensitive identifiers, data integration and privacy engineering.

Data Privacy

The book covers data privacy in depth with respect to data mining, test data management, synthetic data generation etc.

Data Privacy

Author: Nataraj Venkataramanan

Publisher: CRC Press

ISBN: 1498721052

Page: 212

View: 384

The book covers data privacy in depth with respect to data mining, test data management, synthetic data generation etc. It formalizes principles of data privacy that are essential for good anonymization design based on the data format and discipline. The principles outline best practices and reflect on the conflicting relationship between privacy and utility. From a practice standpoint, it provides practitioners and researchers with a definitive guide to approach anonymization of various data formats, including multidimensional, longitudinal, time-series, transaction, and graph data. In addition to helping CIOs protect confidential data, it also offers a guideline as to how this can be implemented for a wide range of data at the enterprise level.

Data Centric Business and Applications

Under EU law, personal data can only be gathered legally under strict conditions, ... In a legal framework data anonymization is regarded as a technological ...

Data Centric Business and Applications

Author: Natalia Kryvinska

Publisher: Springer

ISBN: 3319941178

Page: 330

View: 706

This book discusses processes and procedures in information/data processing and management. The global market is becoming more and more complex with an increased availability of data and information, and as a result doing business with information is becoming more popular, with a significant impact on modern society immensely. This means that there is a growing need for a common understanding of how to create, access, use and manage business information. As such this book explores different aspects of data and information processing, including information generation, representation, structuring, organization, storage, retrieval, navigation, human factors in information systems, and the use of information. It also analyzes the challenges and opportunities of doing business with information, and presents various perspectives on business information managing.

Database Systems for Advanced Applications

To efficiently and incrementally calculate error rates during clustering, we employ a global data structure, i.e. anonymization table.

Database Systems for Advanced Applications

Author: Hiroyuki Kitagawa

Publisher: Springer

ISBN: 3642120989

Page: 485

View: 539

This two volume set LNCS 5981 and LNCS 5982 constitutes the refereed proceedings of the 15th International Conference on Database Systems for Advanced Applications, DASFAA 2010, held in Tsukuba, Japan, in April 2010. The 39 revised full papers and 16 revised short papers presented together with 3 invited keynote papers, 22 demonstration papers, 6 industrial papers, and 2 keynote talks were carefully reviewed and selected from 285 submissions. The papers of the first volume are organized in topical sections on P2P-based technologies, data mining technologies, XML search and matching, graphs, spatial databases, XML technologies, time series and streams, advanced data mining, query processing, Web, sensor networks and communications, information management, as well as communities and Web graphs. The second volume contains contributions related to trajectories and moving objects, skyline queries, privacy and security, data streams, similarity search and event processing, storage and advanced topics, industrial, demo papers, and tutorials and panels.

Advances in Intelligent Information and Database Systems

The new grid is created and the new anonymization area (R2) will totally overlap with the previous anonymization area (R1). In Figure 10b, the vertex C is ...

Advances in Intelligent Information and Database Systems

Author: Ngoc Thanh Nguyen

Publisher: Springer Science & Business Media

ISBN: 364212089X

Page: 384

View: 931

Intelligent information and database systems are two closely related and we- established subfields of modern computer science. They focus on the integration of artificial intelligence and classic database technologies in order to create the class of next generation information systems. The major target of this new gene- tion of systems is to provide end-users with intelligent behavior: simple and/or advanced learning, problem solving, uncertain and certain reasoning, se- organization, cooperation, etc. Such intelligent abilities are implemented in classic information systems to make them autonomous and user oriented, in particular when advanced problems of multimedia information and knowledge discovery, access, retrieval and manipulation are to be solved in the context of large, distr- uted and heterogeneous environments. It means that intelligent knowledge-based information and database systems are used to solve basic problems of large coll- tions management, carry out knowledge discovery from large data collections, reason about information under uncertain conditions, support users in their for- lation of complex queries etc. Topics discussed in this volume include but are not limited to the foundations and principles of data, information, and knowledge models, methodologies for intelligent information and database systems analysis, design, implementation, validation, maintenance and evolution.