The Complete Book of Data Anonymization


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 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.




The Complete Book of Data Anonymization


Book Description

This book on data anonymization could not have come at a better time, given the rapid adoption of outsourcing within enterprises and an ever increasing growth of business data. This book is a must read for enterprise data architects and data managers grappling with the problem of balancing the needs of application outsourcing with the requirements for strong data privacy.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.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.




The Complete Book of Data Anonymization


Book Description

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.Contains extensive criteria grounded in past and current successful projects and activities by experienced Data anonymization practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data anonymization are maximized with professional results.This extraordinary Data anonymization self-assessment will make you the entrusted Data anonymization domain standout by revealing just what you need to know to be fluent and ready for any Data anonymization challenge.







Data Privacy


Book Description

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.




Anonymizing Health Data


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




Database Anonymization


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.




Data Anonymization Complete Self-Assessment Guide


Book Description

Have all basic functions of Data anonymization been defined? What key business process output measure(s) does Data anonymization leverage and how? What other organizational variables, such as reward systems or communication systems, affect the performance of this Data anonymization process? Does the Data anonymization task fit the client's priorities? Is the impact that Data anonymization has shown? This extraordinary Data anonymization self-assessment will make you the entrusted Data anonymization domain standout by revealing just what you need to know to be fluent and ready for any Data anonymization challenge. How do I reduce the effort in the Data anonymization work to be done to get problems solved? How can I ensure that plans of action include every Data anonymization task and that every Data anonymization outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data anonymization costs are low? How can I deliver tailored Data anonymization advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data anonymization essentials are covered, from every angle: the Data anonymization self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data anonymization outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data anonymization practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data anonymization are maximized with professional results. Your purchase includes access details to the Data anonymization self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book.




Data Anonymization A Complete Guide - 2020 Edition


Book Description

What Data anonymization data should be managed? What were the criteria for evaluating a Data anonymization pilot? Can you adapt and adjust to changing Data anonymization situations? Who sets the Data anonymization standards? Think about the functions involved in your Data anonymization project, what processes flow from these functions? This premium Data Anonymization self-assessment will make you the credible Data Anonymization domain visionary by revealing just what you need to know to be fluent and ready for any Data Anonymization challenge. How do I reduce the effort in the Data Anonymization work to be done to get problems solved? How can I ensure that plans of action include every Data Anonymization task and that every Data Anonymization outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Anonymization costs are low? How can I deliver tailored Data Anonymization advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Anonymization essentials are covered, from every angle: the Data Anonymization self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Anonymization outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Anonymization practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Anonymization are maximized with professional results. Your purchase includes access details to the Data Anonymization self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Anonymization Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.




Building an Anonymization Pipeline


Book Description

How can you use data in a way that protects individual privacy but still provides useful and meaningful analytics? With this practical book, data architects and engineers will learn how to establish and integrate secure, repeatable anonymization processes into their data flows and analytics in a sustainable manner. Luk Arbuckle and Khaled El Emam from Privacy Analytics explore end-to-end solutions for anonymizing device and IoT data, based on collection models and use cases that address real business needs. These examples come from some of the most demanding data environments, such as healthcare, using approaches that have withstood the test of time. Create anonymization solutions diverse enough to cover a spectrum of use cases Match your solutions to the data you use, the people you share it with, and your analysis goals Build anonymization pipelines around various data collection models to cover different business needs Generate an anonymized version of original data or use an analytics platform to generate anonymized outputs Examine the ethical issues around the use of anonymized data