Toward A Universal Privacy And Information Preserving Framework For Individual Data Exchange
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Toward A Universal Privacy And Information Preserving Framework For Individual Data Exchange
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Author : Nicolas Ruiz
language : en
Publisher:
Release Date : 2019
Toward A Universal Privacy And Information Preserving Framework For Individual Data Exchange written by Nicolas Ruiz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Data on individual subjects, which are increasingly gathered and exchanged, provide a rich amount of information that can inform statistical and policy analysis in a meaningful way. However, due to the legal obligations surrounding such data, this wealth of information is often not fully exploited in order to protect the confidentiality of respondents. The issue is thus the following: how to ensure a sufficient level of data protection to meet releasers' concerns in terms of legal and ethical requirements, while still offering users a reasonable level of information. This question has raised a range concerns about the privacy/information trade-off and has driven a quest for best practices that can be both useful to users but also respectful of individuals' privacy. Statistical disclosure control research has historically provided the analytical apparatus through which the privacy/information trade-off can be assessed and implemented. In recent years, the literature has burgeoned in many directions. In particular, techniques applicable to micro data offer a wide variety of tools to protect the confidentiality of respondents while maximizing the information content of the data released, for the benefit of society at large. Such diversity is undoubtedly useful but has several major drawbacks. In fact, there is currently a clear lack of agreement and clarity as to the appropriate choice of tools in a given context, and as a consequence, there is no comprehensive view (or at best an incomplete one) of the relative performances of the techniques available. The practical scope of current micro data protection methods is not fully exploited precisely because there is no overarching framework: all methods generally carry their own analytical environment, underlying approaches and definitions of privacy and information. Moreover, the evaluation of utility and privacy for each method is metric and data-dependent, meaning that comparisons across different methods and datasets is a daunting task. Against this backdrop, this thesis focuses on establishing some common grounds for individual data anonymization by developing a new, universal approach. Recent contributions to the literature point to the fact that permutations happen to be the essential principle upon which individual data anonymization can be based. In this thesis, we demonstrate that this principle allows for the proposal of a universal analytical environment for data anonymization. The first contribution of this thesis takes an ex-post approach by proposing some universal measures of disclosure risk and information loss that can be computed in a simple fashion and used for the evaluation of any anonymization method, independently of the context under which they operate. In particular, they exhibit distributional independence. These measures establish a common language for comparing different mechanisms, all with potentially varying parametrizations applied to the same data set or to different data sets. The second contribution of this thesis takes an ex-ante approach by developing a new approach to data anonymization. Bringing data anonymization closer to cryptography, it formulates a general cipher based on permutation keys which appears to be equivalent to a general form of rank swapping. Beyond all the existing methods that this cipher can universally reproduce, it also offers a new way to practice data anonymization based on the ex-ante exploration of different permutation structures. The subsequent study of the cipher's properties additionally reveals new insights as to the nature of the task of anonymization taken at a general level of functioning. The final two contributions of this thesis aim at exploring two specific areas using the above results. The first area is longitudinal data anonymization. Despite the fact that the SDC literature offers a wide variety of tools suited to different contexts and data types, there have been very few attempts to deal with the challenges posed by longitudinal data. This thesis thus develops a general framework and some associated metrics of disclosure risk and information loss, tailored to the specific challenges posed by longitudinal data anonymization. Notably, it builds on a permutation approach where the effect of time on time-variant attributes can be seen as an anonymization method that can be captured by temporal permutations. The second area considered is synthetic data. By challenging the information and privacy guarantees of synthetic data, it is shown that any synthetic data set can always be expressed as a permutation of the original data, in a way similar to non-synthetic SDC techniques. In fact, releasing synthetic data sets with the same privacy properties but with an improved level of information appears to be invariably possible as the marginal distributions can always be preserved without increasing risk. On the privacy front, this leads to the consequence that the distinction drawn in the literature between non-synthetic and synthetic data is not so clear-cut. Indeed, it is shown that the practice of releasing several synthetic data sets for a single original data set entails privacy issues that do not arise in non-synthetic anonymization.
Towards Secure And Privacy Preserving E Health Data Exchanges Through Consent Based Access Control
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Author : Abel Bradley Saed Bacchus
language : en
Publisher:
Release Date : 2017
Towards Secure And Privacy Preserving E Health Data Exchanges Through Consent Based Access Control written by Abel Bradley Saed Bacchus and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
How we administer healthcare continues to evolve alongside the advancement of information technology. As we become more connected, the Internet of Things and our want to share information in a timely manner encourage us to redefine and enhance how we exchange health information. A fully integrated, universal health record system in Canada remains a distant goal. It requires thoughtful legislation, sufficient resources and the best of our technological and security implementation before realization. Nevertheless, we need such a system and are steadily working towards it. While there are a number of obstacles in attempting a universal health record system, this thesis presents a solution for secure health information exchanges. A valuable component in establishing a complete framework for all health information exchanges. We present two protocols. Consent based access control (CBAC) and a fairness aware privacy preservation protocol (FAPP). These two protocols grant patients control in how their sensitive health information is used and provides avenues for certain third parties to collect patient information without compromising security and privacy.
Towards A Privacy Preserving Framework For Publishing Longitudinal Data
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Author : Morvarid Sehatkar
language : en
Publisher:
Release Date : 2014
Towards A Privacy Preserving Framework For Publishing Longitudinal Data written by Morvarid Sehatkar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Data protection categories.
Recent advances in information technology have enabled public organizations and corporations to collect and store huge amounts of individuals' data in data repositories. Such data are powerful sources of information about an individual's life such as interests, activities, and finances. Corporations can employ data mining and knowledge discovery techniques to extract useful knowledge and interesting patterns from large repositories of individuals' data. The extracted knowledge can be exploited to improve strategic decision making, enhance business performance, and improve services. However, person-specific data often contain sensitive information about individuals and publishing such data poses potential privacy risks. To deal with these privacy issues, data must be anonymized so that no sensitive information about individuals can be disclosed from published data while distortion is minimized to ensure usefulness of data in practice. In this thesis, we address privacy concerns in publishing longitudinal data. A data set is longitudinal if it contains information of the same observation or event about individuals collected at several points in time. For instance, the data set of multiple visits of patients of a hospital over a period of time is longitudinal. Due to temporal correlations among the events of each record, potential background knowledge of adversaries about an individual in the context of longitudinal data has specific characteristics. None of the previous anonymization techniques can effectively protect longitudinal data against an adversary with such knowledge. In this thesis we identify the potential privacy threats on longitudinal data and propose a novel framework of anonymization algorithms in a way that protects individuals' privacy against both identity disclosure and attribute disclosure, and preserves data utility. Particularly, we propose two privacy models: (K, C)P̂ -privacy and (K, C)-privacy, and for each of these models we propose efficient algorithms for anonymizing longitudinal data. An extensive experimental study demonstrates that our proposed framework can effectively and efficiently anonymize longitudinal data.
New Models And Techniques On Privacy Preserving Information Sharing
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Author : Yabo Xu
language : en
Publisher:
Release Date : 2008
New Models And Techniques On Privacy Preserving Information Sharing written by Yabo Xu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computer networks categories.
Due to the wide deployment of Internet and information technology, the ever growing privacy concern has been a major obstacle for information sharing. This thesis work thus centres on developing new models and techniques to deal with emerging privacy issues in various contexts of information sharing and exchange. Specifically, along with the main theme, this thesis work can be divided into three categories, summarized as follows. The first problem is privacy-preserving data mining spanning multiple private data sources. The goal of this research is to enable the computation as the data collected in a central place, but preserve the privacy of participating sites. This problem has been studied in the context of classification with multiple private data sources integrated with join semantics. The second problem privacy-preserving data publishing. This research aims to address the scenario where a data owner wishes to publish the data while preserving individual privacy. This topic has been extensively studied in the context of relational data, but much less is known for transaction data. We propose one way to address this issue in this thesis. The third problem is privacy-enhancing online personalized service. This research starts from an end user's point of view, and studies how to submit a piece of personal data to exchange for service without compromising individual privacy. Our contribution on this topic is a framework under which individual users can strike a balance between service quality and privacy protection.
Privacy Preserving Data Publishing
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Author : Bee-Chung Chen
language : en
Publisher: Now Publishers Inc
Release Date : 2009-10-14
Privacy Preserving Data Publishing written by Bee-Chung Chen and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-14 with Data mining categories.
This book is dedicated to those who have something to hide. It is a book about "privacy preserving data publishing" -- the art of publishing sensitive personal data, collected from a group of individuals, in a form that does not violate their privacy. This problem has numerous and diverse areas of application, including releasing Census data, search logs, medical records, and interactions on a social network. The purpose of this book is to provide a detailed overview of the current state of the art as well as open challenges, focusing particular attention on four key themes: RIGOROUS PRIVACY POLICIES Repeated and highly-publicized attacks on published data have demonstrated that simplistic approaches to data publishing do not work. Significant recent advances have exposed the shortcomings of naive (and not-so-naive) techniques. They have also led to the development of mathematically rigorous definitions of privacy that publishing techniques must satisfy; METRICS FOR DATA UTILITY While it is necessary to enforce stringent privacy policies, it is equally important to ensure that the published version of the data is useful for its intended purpose. The authors provide an overview of diverse approaches to measuring data utility; ENFORCEMENT MECHANISMS This book describes in detail various key data publishing mechanisms that guarantee privacy and utility; EMERGING APPLICATIONS The problem of privacy-preserving data publishing arises in diverse application domains with unique privacy and utility requirements. The authors elaborate on the merits and limitations of existing solutions, based on which we expect to see many advances in years to come.
The Algorithmic Foundations Of Differential Privacy
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Author : Cynthia Dwork
language : en
Publisher:
Release Date : 2014
The Algorithmic Foundations Of Differential Privacy written by Cynthia Dwork and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computers categories.
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.
Universal Health Coin
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Author : Dr. Gordon Jones
language : en
Publisher: AuthorHouse
Release Date : 2017-12-22
Universal Health Coin written by Dr. Gordon Jones and has been published by AuthorHouse this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Young Adult Nonfiction categories.
Would you like to be a part of a movement to create the ultimate universal health system worldwide? We cant do it without you! Due to the emergence of the blockchain and cryptocurrency technology, we now have the ability to completely reinvent the way healthcare is financed and paid for worldwide. Join us by going to www.UniversalHealthCoin.com.
Protecting Individual Privacy In The Struggle Against Terrorists
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2008-10-26
Protecting Individual Privacy In The Struggle Against Terrorists written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-26 with Computers categories.
All U.S. agencies with counterterrorism programs that collect or "mine" personal data-such as phone records or Web sites visited-should be required to evaluate the programs' effectiveness, lawfulness, and impacts on privacy. A framework is offered that agencies can use to evaluate such information-based programs, both classified and unclassified. The book urges Congress to re-examine existing privacy law to assess how privacy can be protected in current and future programs and recommends that any individuals harmed by violations of privacy be given a meaningful form of redress. Two specific technologies are examined: data mining and behavioral surveillance. Regarding data mining, the book concludes that although these methods have been useful in the private sector for spotting consumer fraud, they are less helpful for counterterrorism because so little is known about what patterns indicate terrorist activity. Regarding behavioral surveillance in a counterterrorist context, the book concludes that although research and development on certain aspects of this topic are warranted, there is no scientific consensus on whether these techniques are ready for operational use at all in counterterrorism.
Configuring The Networked Self
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Author : Julie E. Cohen
language : en
Publisher: Yale University Press
Release Date : 2012-01-24
Configuring The Networked Self written by Julie E. Cohen and has been published by Yale University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-24 with Law categories.
The legal and technical rules governing flows of information are out of balance, argues Julie E. Cohen in this original analysis of information law and policy. Flows of cultural and technical information are overly restricted, while flows of personal information often are not restricted at all. The author investigates the institutional forces shaping the emerging information society and the contradictions between those forces and the ways that people use information and information technologies in their everyday lives. She then proposes legal principles to ensure that people have ample room for cultural and material participation as well as greater control over the boundary conditions that govern flows of information to, from, and about them.
Cyber Crime Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2011-11-30
Cyber Crime Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-30 with Computers categories.
Threatening the safety of individuals, computers, and entire networks, cyber crime attacks vary in severity and type. Studying this continually evolving discipline involves not only understanding different types of attacks, which range from identity theft to cyberwarfare, but also identifying methods for their prevention. Cyber Crime: Concepts, Methodologies, Tools and Applications is a three-volume reference that explores all aspects of computer-based crime and threats, offering solutions and best practices from experts in software development, information security, and law. As cyber crime continues to change and new types of threats emerge, research focuses on developing a critical understanding of different types of attacks and how they can best be managed and eliminated.