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Author: Khaled El Emam Publisher: "O'Reilly Media, Inc." ISBN: 1449363032 Category : Computers Languages : en Pages : 252
Book Description
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
Author: Khaled El Emam Publisher: "O'Reilly Media, Inc." ISBN: 1449363032 Category : Computers Languages : en Pages : 252
Book Description
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
Author: Josep Domingo-Ferrer Publisher: Springer Nature ISBN: 3031023471 Category : Computers Languages : en Pages : 120
Book Description
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.
Author: Balaji Raghunathan Publisher: CRC Press ISBN: 1439877319 Category : Computers Languages : en Pages : 267
Book Description
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
Author: Josep Domingo-Ferrer Publisher: Morgan & Claypool Publishers ISBN: 1627058443 Category : Computers Languages : en Pages : 138
Book Description
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.
Author: Weiyi Meng Publisher: Springer ISBN: 3642374875 Category : Computers Languages : en Pages : 509
Book Description
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.
Author: Weitong Chen Publisher: Springer Nature ISBN: 3031221370 Category : Computers Languages : en Pages : 500
Book Description
The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Author: Aris Gkoulalas-Divanis Publisher: Springer Science & Business Media ISBN: 1461456673 Category : Medical Languages : en Pages : 87
Book Description
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.
Book Description
Security mechanisms like encryption negatively affect other software quality characteristics like efficiency. To cope with such trade-offs, it is preferable to build approaches that allow to tune the trade-offs after the implementation and design phase. This book introduces a methodology that can be used to build such tunable approaches. The book shows how the proposed methodology can be applied in the domains of database outsourcing, identity management, and credential management.
Author: Joaquin Garcia-Alfaro Publisher: Springer ISBN: 3030003051 Category : Computers Languages : en Pages : 445
Book Description
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.
Author: Erich Schweighofer Publisher: Springer ISBN: 3319672800 Category : Computers Languages : en Pages : 241
Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 5th Annual Privacy Forum, APF 2017, held in Vienna, Austria, in June 2017. The 12 revised full papers were carefully selected from 41 submissions on the basis of significance, novelty, and scientific quality. These selected papers are organized in three different chapters corresponding to the conference sessions. The first chapter, “Data Protection Regulation”, discusses topics concerning big genetic data, a privacy-preserving European identity ecosystem, the right to be forgotten und the re-use of privacy risk analysis. The second chapter, “Neutralisation and Anonymization”, discusses neutralisation of threat actors, privacy by design data exchange between CSIRTs, differential privacy and database anonymization. Finally, the third chapter, “Privacy Policies in Practice”, discusses privacy by design, privacy scores, privacy data management in healthcare and trade-offs between privacy and utility.
Author: Khaled El Emam
Author: Khaled El Emam
Author: Josep Domingo-Ferrer
Author: Balaji Raghunathan
Author: Josep Domingo-Ferrer
Author: Weiyi Meng
Author: Weitong Chen
Author: Aris Gkoulalas-Divanis
Author: Koehler, Jens
Author: Joaquin Garcia-Alfaro
Author: Erich Schweighofer