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1

Zhang, Nan. "Privacy-preserving data mining." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1080.

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2

Nguyen, Benjamin. "Privacy-Centric Data Management." Habilitation à diriger des recherches, Université de Versailles-Saint Quentin en Yvelines, 2013. http://tel.archives-ouvertes.fr/tel-00936130.

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This document will focus on my core computer science research since 2010, covering the topic of data management and privacy. More speci cally, I will present the following topics : -ˆ A new paradigm, called Trusted Cells for privacy-centric personal data management based on the Asymmetric Architecture composed of trusted or open (low power) distributed hardware devices acting as personal data servers and a highly powerful, highly available supporting server, such as a cloud. (Chapter 2). ˆ- Adapting aggregate data computation techniques to the Trusted Cells environment, with the example of Pri
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3

Lin, Zhenmin. "Privacy Preserving Distributed Data Mining." UKnowledge, 2012. http://uknowledge.uky.edu/cs_etds/9.

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Privacy preserving distributed data mining aims to design secure protocols which allow multiple parties to conduct collaborative data mining while protecting the data privacy. My research focuses on the design and implementation of privacy preserving two-party protocols based on homomorphic encryption. I present new results in this area, including new secure protocols for basic operations and two fundamental privacy preserving data mining protocols. I propose a number of secure protocols for basic operations in the additive secret-sharing scheme based on homomorphic encryption. I derive a basi
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4

Aron, Yotam. "Information privacy for linked data." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85215.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 77-79).<br>As data mining over massive amounts of linked data becomes more and more prevalent in research applications, information privacy becomes a more important issue. This is especially true in the biological and medica
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5

Jawad, Mohamed. "Data privacy in P2P Systems." Nantes, 2011. http://www.theses.fr/2011NANT2020.

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Les communautés en ligne pair-a-pair (P2P), comme les communautés professionnelles (p. Ex. , médicales ou de recherche) deviennent de plus en plus populaires a cause de l’augmentation des besoins du partage de données. Alors que les environnements P2P offrent des caractéristiques intéressantes (p. Ex. , passage a l’échelle, disponibilité, dynamicité), leurs garanties en termes de protection des données sensibles sont limitées. Ils peuvent être considérés comme hostiles car les données publiées peuvent être consultées par tous les pairs (potentiellement malicieux) et utilisées pour tout (p. Ex.
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6

Foresti, S. "Preserving privacy in data outsourcing." Doctoral thesis, Università degli Studi di Milano, 2010. http://hdl.handle.net/2434/156360.

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Privacy requirements have an increasing impact on the realization of modern applications. Commercial and legal regulations demand that privacy guarantees be provided whenever sensitive information is stored, processed, or communicated to external parties. Current approaches encrypt sensitive data, thus reducing query execution efficiency and preventing selective information release. In this thesis, we present a comprehensive approach for protecting highly sensitive information when it is stored on systems that are not under the data owner's control. Our approach combines access control
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7

Livraga, G. "PRESERVING PRIVACY IN DATA RELEASE." Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233324.

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Data sharing and dissemination play a key role in our information society. Not only do they prove to be advantageous to the involved parties, but they can also be fruitful to the society at large (e.g., new treatments for rare diseases can be discovered based on real clinical trials shared by hospitals and pharmaceutical companies). The advancements in the Information and Communication Technology (ICT) make the process of releasing a data collection simpler than ever. The availability of novel computing paradigms, such as data outsourcing and cloud computing, make scalable, reliable and fast i
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8

Loukides, Grigorios. "Data utility and privacy protection in data publishing." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54743/.

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Data about individuals is being increasingly collected and disseminated for purposes such as business analysis and medical research. This has raised some privacy concerns. In response, a number of techniques have been proposed which attempt to transform data prior to its release so that sensitive information about the individuals contained within it is protected. A:-Anonymisation is one such technique that has attracted much recent attention from the database research community. A:-Anonymisation works by transforming data in such a way that each record is made identical to at least A: 1 other
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9

Sobati, Moghadam Somayeh. "Contributions to Data Privacy in Cloud Data Warehouses." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2020.

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Actuellement, les scénarios d’externalisation de données deviennent de plus en plus courants avec l’avènement de l’infonuagique. L’infonuagique attire les entreprises et les organisations en raison d’une grande variété d’avantages fonctionnels et économiques.De plus, l’infonuagique offre une haute disponibilité, le passage d’échelle et une reprise après panne efficace. L’un des services plus notables est la base de données en tant que service (Database-as-a-Service), où les particuliers et les organisations externalisent les données, le stockage et la gestion `a un fournisseur de services. Ces
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10

Bonatti, Piero A., Bert Bos, Stefan Decker, et al. "Data Privacy Vocabularies and Controls: Semantic Web for Transparency and Privacy." CEUR Workshop Proceedings, 2018. http://epub.wu.ac.at/6490/1/SW4SG_2018.pdf.

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Managing Privacy and understanding the handling of personal data has turned into a fundamental right¿at least for Europeans since May 25th with the coming into force of the General Data Protection Regulation. Yet, whereas many different tools by different vendors promise companies to guarantee their compliance to GDPR in terms of consent management and keeping track of the personal data they handle in their processes, interoperability between such tools as well uniform user facing interfaces will be needed to enable true transparency, user-configurable and -manageable privacy policies and data
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11

Ma, Jianjie. "Learning from perturbed data for privacy-preserving data mining." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/Summer2006/j%5Fma%5F080406.pdf.

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12

Swapna, B., and R. VijayaPrakash. "Privacy Preserving Data Mining Operations without Disrupting Data Quality." International Journal of Computer Science and Network (IJCSN), 2012. http://hdl.handle.net/10150/271473.

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Data mining operations have become prevalent as they can extract trends or patterns that help in taking good business decisions. Often they operate on large historical databases or data warehouses to obtain actionable knowledge or business intelligence that helps in taking well informed decisions. In the data mining domain there came many tools to perform data mining operations. These tools are best used to obtain actionable knowledge from data. Manually doing this is not possible as the data is very huge and takes lot of time. Thus the data mining domain is being improved in a rapid
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13

Heerde, Harold Johann Wilhelm van. "Privacy-aware data management by means of data degradation." Versailles-St Quentin en Yvelines, 2010. http://www.theses.fr/2010VERS0031.

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Les fournisseurs de services recueillent de plus en plus d'informations personnelles sensibles, bien qu’il soit réputé comme très difficile de protéger efficacement ces informations contre le pira-tage, la fuite d’information par négligence, le contournement de chartes de confidentialité peu précises, et les usages abusifs d’administrateurs de données peu scrupuleux. Dans cette thèse, nous conjecturons qu’une rétention sans limite de données sensibles dans une base de données mènera inévitablement à une divulgation non autorisée de ces données. Limiter dans le temps la rétention d'informations
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14

Ataei, Mehrnaz. "Location data privacy : principles to practice." Doctoral thesis, Universitat Jaume I, 2018. http://hdl.handle.net/10803/666740.

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A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information Systems<br>Location data is essential to the provision of relevant and tailored information in location-based services (LBS) but has the potential to reveal sensitive information about users. Unwanted disclosure of location data is associated with various threats known as dataveillance which can lead to risks like loss of control, (continuous) monitoring, identification, and social profiling. Striking a balance between providing a serv
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15

Sivakumar, Anusha. "Enhancing Privacy Of Data Through Anonymization." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177349.

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A steep rise in availability of personal data has resulted in endless opportunities for data scientists who utilize this open data for research. However, such easy availability of complex personal data challenges privacy of individuals represented in the data. To protect privacy, traditional methods such as using pseudonyms or blurring identity of individuals are followed before releasing data. These traditional methods alone are not sufficient to enhance privacy because combining released data with other publicly available data or background knowledge identifies individuals. A potential solut
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16

Sang, Lin. "Social Big Data and Privacy Awareness." Thesis, Uppsala universitet, Institutionen för informatik och media, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242444.

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Based on the rapid development of Big Data, the data from the online social network becomea major part of it. Big data make the social networks became data-oriented rather than social-oriented. Taking this into account, this dissertation presents a qualitative study to research howdoes the data-oriented social network affect its users’ privacy management for nowadays. Within this dissertation, an overview of Big Data and privacy issues on the social network waspresented as a background study. We adapted the communication privacy theory as a frameworkfor further analysis how individuals manage t
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17

Lazarovich, Amir. "Invisible Ink : blockchain for data privacy." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98626.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 81-85).<br>The problem of maintaining complete control over and transparency with regard to our digital identity is growing more urgent as our lives become more dependent on online and digital services. What once was rightfully ours and under our control is now spread among uncountable entities across many locations. We have built a platform that securely distributes encrypted u
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18

DeYoung, Mark E. "Privacy Preserving Network Security Data Analytics." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82909.

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The problem of revealing accurate statistics about a population while maintaining privacy of individuals is extensively studied in several related disciplines. Statisticians, information security experts, and computational theory researchers, to name a few, have produced extensive bodies of work regarding privacy preservation. Still the need to improve our ability to control the dissemination of potentially private information is driven home by an incessant rhythm of data breaches, data leaks, and privacy exposure. History has shown that both public and private sector organizations are no
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19

Shang, Hui. "Privacy Preserving Kin Genomic Data Publishing." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1594835227299524.

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20

Lin, Zehua. "Privacy Preserving Social Network Data Publishing." Miami University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=miami1610045108271476.

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21

Gonçalves, João Miguel Ribeiro. "Context-awareness privacy in data communications." Doctoral thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/15760.

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Doutoramento em Informática<br>Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed
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22

Thomas, Dilys. "Algorithms and architectures for data privacy /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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23

Smith, Tanshanika Turner. "Examining Data Privacy Breaches in Healthcare." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2623.

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Healthcare data can contain sensitive, personal, and confidential information that should remain secure. Despite the efforts to protect patient data, security breaches occur and may result in fraud, identity theft, and other damages. Grounded in the theoretical backdrop of integrated system theory, the purpose of this study was to determine the association between data privacy breaches, data storage locations, business associates, covered entities, and number of individuals affected. Study data consisted of secondary breach information retrieved from the Department of Health and Human Services
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24

Zheng, Yao. "Privacy Preservation for Cloud-Based Data Sharing and Data Analytics." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73796.

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Data privacy is a globally recognized human right for individuals to control the access to their personal information, and bar the negative consequences from the use of this information. As communication technologies progress, the means to protect data privacy must also evolve to address new challenges come into view. Our research goal in this dissertation is to develop privacy protection frameworks and techniques suitable for the emerging cloud-based data services, in particular privacy-preserving algorithms and protocols for the cloud-based data sharing and data analytics services. Cloud co
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25

de, Souza Tulio. "Data-level privacy through data perturbation in distributed multi-application environments." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:2b818039-bde4-41d6-96ca-0367704a53f0.

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Wireless sensor networks used to have a main role as a monitoring tool for environmental purposes and animal tracking. This spectrum of applications, however, has dramatically grown in the past few years. Such evolution means that what used to be application-specific networks are now multi application environments, often with federation capabilities. This shift results in a challenging environment for data privacy, mainly caused by the broadening of the spectrum of data access points and involved entities. This thesis first evaluates existing privacy preserving data aggregation techniques to d
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Stouppa, Phiniki. "Deciding Data Privacy for ALC Knowledge Bases /." [S.l.] : [s.n.], 2009. http://www.ub.unibe.ch/content/bibliotheken_sammlungen/sondersammlungen/dissen_bestellformular/index_ger.html.

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27

Balla, Stefano. "Privacy-Preserving Data Mining: un approccio verticale." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17517/.

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La crescente disponibilità dei dati, oltre a portare grandi benefici, ha portato alla luce diversi rischi dipendenti dell'esposizione di informazioni confidenziali. Inoltre il metodo di estrazione di informazioni detto Data Mining ha posto un ulteriore problema dando la possibilità di estrarre informazioni sensibili. Questa tesi tratta il tema della privacy sotto tre livelli principali: Privacy-Preserving Data Providing, Privacy-Preserving Data Collecting e Privacy-Preserving Data Mining. Questi livelli rappresentano la divisione del ciclo dei dati in tre tappe in cui i dati prima vengono fo
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Chen, Xiaoqiang. "Privacy Preserving Data Publishing for Recommender System." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155785.

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Driven by mutual benefits, exchange and publication of data among various parties is an inevitable trend. However, released data often contains sensitive information thus direct publication violates individual privacy. This undertaking is in the scope of privacy preserving data publishing (PPDP). Among many privacy models, K- anonymity framework is popular and well-studied, it protects data by constructing groups of anonymous records such that each record in the table released is covered by no fewer than k-1 other records. This thesis investigates different privacy models and focus on achievin
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29

Scheffler, Thomas. "Privacy enforcement with data owner-defined policies." Phd thesis, Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6793/.

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This thesis proposes a privacy protection framework for the controlled distribution and use of personal private data. The framework is based on the idea that privacy policies can be set directly by the data owner and can be automatically enforced against the data user. Data privacy continues to be a very important topic, as our dependency on electronic communication maintains its current growth, and private data is shared between multiple devices, users and locations. The growing amount and the ubiquitous availability of personal private data increases the likelihood of data misuse. Early pr
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30

Sweatt, Brian M. (Brian Michael). "A privacy-preserving personal sensor data ecosystem." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91875.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 79-82).<br>Despite the ubiquity of passively-collected sensor data (primarily attained via smartphones), there does not currently exist a comprehensive system for authorizing the collection of such data, collecting, storing, analyzing, and visualizing it in a manner that preserves the privacy of the user generating the data. This thesis shows the design and implementation of such a system,
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Paradesi, Sharon M. (Sharon Myrtle) 1986. "User-controlled privacy for personal mobile data." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/93839.

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Thesis: Elec. E. in Computer Science, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 81-82).<br>Smartphones collect a wide range of sensor data, ranging from the basic, such as location, accelerometer, and Bluetooth, to the more advanced, such as heart rate. Mobile apps on the Android and iOS platforms provide users with "all-or-nothing" controls during installation to get permission for data collection and use. Users have to either agree to have the a
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Simmons, Sean Kenneth. "Preserving patient privacy in biomedical data analysis." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101821.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 147-154).<br>The growing number of large biomedical databases and electronic health records promise to be an invaluable resource for biomedical researchers. Recent work, however, has shown that sharing this data- even when aggregated to produce p-values, regression coefficients, count queries, and minor allele frequencies (MAFs)- may compromise patient privacy. This raises a fundamental question: how do we protect patient
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33

Mittal, Nupur. "Data, learning and privacy in recommendation systems." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S084/document.

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Les systèmes de recommandation sont devenus une partie indispensable des services et des applications d’internet, en particulier dû à la surcharge de données provenant de nombreuses sources. Quel que soit le type, chaque système de recommandation a des défis fondamentaux à traiter. Dans ce travail, nous identifions trois défis communs, rencontrés par tous les types de systèmes de recommandation: les données, les modèles d'apprentissage et la protection de la vie privée. Nous élaborons différents problèmes qui peuvent être créés par des données inappropriées en mettant l'accent sur sa qualité e
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34

Keerthi, Thomas. "Distilling mobile privacy requirements from qualitative data." Thesis, Open University, 2014. http://oro.open.ac.uk/40121/.

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As mobile computing applications have become commonplace, it is increasingly important for them to address end-users' privacy requirements. Mobile privacy requirements depend on a number of contextual socio-cultural factors to which mobility adds another level of contextual variation. However, traditional requirements elicitation methods do not sufficiently account for contextual factors and therefore cannot be used effectively to represent and analyse the privacy requirements of mobile end users. On the other hand, methods that investigate contextual factors tend to produce data which can be
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Ainslie, Mandi. "Big data and privacy : a modernised framework." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/59805.

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Like the revolutions that preceded it, the Fourth Industrial Revolution has the potential to raise global income levels and improve the quality of life for populations around the world. Responding to global challenges, generating efficiencies, prediction improvement, democratisation access to information and empowering individuals are a few examples of the economic and social value created by personal information. However, this technological innovation, efficiency and productivity comes at a price -?privacy. As a result, individuals are growingly concerned that companies and governments are n
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Nan, Lihao. "Privacy Preserving Representation Learning For Complex Data." Thesis, The University of Sydney, 2019. http://hdl.handle.net/2123/20662.

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Here we consider a common data encryption problem encountered by users who want to disclose some data to gain utility but preserve their private information. Specifically, we consider the inference attack, in which an adversary conducts inference on the disclosed data to gain information about users' private data. Following privacy funnel \cite{makhdoumi2014information}, assuming that the original data $X$ is transformed into $Z$ before disclosing and the log loss is used for both privacy and utility metrics, then the problem can be modeled as finding a mapping $X \rightarrow Z$ that maximizes
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Liyanaarachchi, Gajendra P. "Data Privacy Considerations for Redesigning Organizational Strategy." Thesis, Griffith University, 2022. http://hdl.handle.net/10072/417671.

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The thesis consists of eight interrelated chapters. The introduction chapter provides an overview of the thesis topic, summarizes the gaps in the existing knowledge, and describes the research's purpose, context, and design. The second chapter includes paper 1, which focuses on identifying the rationale and antecedents for the personal privacy concerns that lead to the Privacy paradox. The third chapter comprises paper 2, which focuses on personal privacy concerns to segment the customers and design sales strategies in online banking. The fourth chapter includes paper 3, which focuses on perso
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Huang, Xueli. "Achieving Data Privacy and Security in Cloud." Diss., Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/372805.

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Computer and Information Science<br>Ph.D.<br>The growing concerns in term of the privacy of data stored in public cloud have restrained the widespread adoption of cloud computing. The traditional method to protect the data privacy is to encrypt data before they are sent to public cloud, but heavy computation is always introduced by this approach, especially for the image and video data, which has much more amount of data than text data. Another way is to take advantage of hybrid cloud by separating the sensitive data from non-sensitive data and storing them in trusted private cloud and un-trus
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Lebrun, Thomas. "Health data : Exploring emerging privacy enhancing mechanisms." Electronic Thesis or Diss., Lyon, INSA, 2024. http://www.theses.fr/2024ISAL0114.

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Les données de santé représentent une grande quantité d'informations, générées quotidiennement et sensibles par nature. Cependant, leur partage est essentiel pour l'avancement de la recherche et, en fin de compte, l'amélioration des soins aux patients. L’utilisation des données médicales est confrontée à des limitations dues à leur sensibilité et à la nécessité de garantir la confidentialité, encadrée par les réglementations en vigueur. Cela nécessite une protection renforcée. L’intérêt pour des alternatives au partage de données brutes, telles que la pseudonymisation ou l’anonymisation, augme
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40

Huang, Zhengli. "Privacy and utility analysis of the randomization approach in Privacy-Preserving Data Publishing." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2008. http://wwwlib.umi.com/cr/syr/main.

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Fernandez, Garcia Javier D., Fajar J. Ekaputra, Peb Ruswono Aryan, Amr Azzam, and Elmar Kiesling. "Privacy-aware Linked Widgets." ACM Press, 2019. http://epub.wu.ac.at/6859/1/Privacy_aware_Linked_Data_Widgets___WWW_19__Camera_Ready.pdf.

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The European General Data Protection Regulation (GDPR) brings new challenges for companies, who must demonstrate that their systems and business processes comply with usage constraints specified by data subjects. However, due to the lack of standards, tools, and best practices, many organizations struggle to adapt their infrastructure and processes to ensure and demonstrate that all data processing is in compliance with users' given consent. The SPECIAL EU H2020 project has developed vocabularies that can formally describe data subjects' given consent as well as methods that use this
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42

Brown, Emily Elizabeth. "Adaptable Privacy-preserving Model." Diss., NSUWorks, 2019. https://nsuworks.nova.edu/gscis_etd/1069.

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Current data privacy-preservation models lack the ability to aid data decision makers in processing datasets for publication. The proposed algorithm allows data processors to simply provide a dataset and state their criteria to recommend an xk-anonymity approach. Additionally, the algorithm can be tailored to a preference and gives the precision range and maximum data loss associated with the recommended approach. This dissertation report outlined the research’s goal, what barriers were overcome, and the limitations of the work’s scope. It highlighted the results from each experiment conducted
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43

Olsson, Mattias. "Klassificeringsalgoritmer vs differential privacy : Effekt på klassificeringsalgoritmer vid användande av numerisk differential privacy." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15680.

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Data mining är ett samlingsnamn för ett antal tekniker som används för att analysera datamängder och finna mönster, exempelvis genom klassificering. Anonymisering innefattar en rad tekniker för att skydda den personliga integriteten. Den här studien undersöker hur stor påverkansgrad anonymisering med tekniken differential privacy har på möjligheten att klassificera en datamängd. Genom ett experiment undersöks ett antal magnituder av anonymisering och vilken effekt de har på möjligheten att klassificera data. Klassificering av den anonymiserade datamängden jämförs mot klassificering av den råa
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ABU, HASHISH IMAN HISHAM JAMIL. "Applied Data Science Approaches in FinTech: Innovative Models for Bitcoin Price Dynamics." Doctoral thesis, Università degli studi di Pavia, 2020. http://hdl.handle.net/11571/1326028.

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Living in a data-intensive environment is a natural consequence to the continuous innovations and technological advancements, that created countless opportunities for addressing domain-specific challenges following the Data Science approach. The main objective of this thesis is to present applied Data Science approaches in FinTech, focusing on proposing innovative descriptive and predictive models for studying and exploring Bitcoin Price Dynamics and Bitcoin Price Prediction. With reference to the research area of Bitcoin Price Dynamics, two models are proposed. The first model is a Network Ve
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Stroud, Caleb Zachary. "Implementing Differential Privacy for Privacy Preserving Trajectory Data Publication in Large-Scale Wireless Networks." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/84548.

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Wireless networks collect vast amounts of log data concerning usage of the network. This data aids in informing operational needs related to performance, maintenance, etc., but it is also useful for outside researchers in analyzing network operation and user trends. Releasing such information to these outside researchers poses a threat to privacy of users. The dueling need for utility and privacy must be addressed. This thesis studies the concept of differential privacy for fulfillment of these goals of releasing high utility data to researchers while maintaining user privacy. The focus is spe
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Sallaku, Redlon <1994&gt. "Privacy and Protecting Privacy: Using Static Analysis for legal compliance. General Data Protection Regulation." Master's Degree Thesis, Università Ca' Foscari Venezia, 2019. http://hdl.handle.net/10579/14682.

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The main purpose of the thesis is to study Privacy and how protecting Privacy, including the new regulation framework proposed by EU the GDPR, investigating how static analysis could help GDPR enforcement, and develop a new static analysis prototype to fulfill this task in practice. GDPR (General Data Protection Regulation) is a recent European regulation to harmonize and enforce data privacy laws across Europe, to protect and empower all EU citizens data privacy, and to reshape the way organizations deal with sensitive data. This regulation has been enforced starting from May 2018. While it i
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Sehatkar, Morvarid. "Towards a Privacy Preserving Framework for Publishing Longitudinal Data." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31629.

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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, pe
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Casas, Roma Jordi. "Privacy-preserving and data utility in graph mining." Doctoral thesis, Universitat Autònoma de Barcelona, 2014. http://hdl.handle.net/10803/285566.

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En los últimos años, ha sido puesto a disposición del público una gran cantidad de los datos con formato de grafo. Incrustado en estos datos hay información privada acerca de los usuarios que aparecen en ella. Por lo tanto, los propietarios de datos deben respetar la privacidad de los usuarios antes de liberar los conjuntos de datos a terceros. En este escenario, los procesos de anonimización se convierten en un proceso muy importante. Sin embargo, los procesos de anonimización introducen, generalmente, algún tipo de ruido en los datos anónimos y también en sus resultados en procesos de mine
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Rodríguez, García María Mercedes. "Semantic perturbative privacy-preserving methods for nominal data." Doctoral thesis, Universitat Rovira i Virgili, 2017. http://hdl.handle.net/10803/435689.

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L’explotació de microdades personals (p. ex., dades censals, preferències, o registres de salut) és de gran interès per a la mineria de dades. Aquestes dades sovint contenen informació sensible que pot ser directament o indirectament relacionada amb els individus. Per tant, cal implementar mesures per a preservar la privadesa i minimitzar el risc de re-identificació i, conseqüentment, de revelació d’informació confidencial sobre els individus. Tot i que s’han desenvolupat nombroses mètodes per preservar la privadesa de dades numèriques, la protecció de valors nominals ha rebut escassa atenció.
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An, Nan. "Protect Data Privacy in E-Healthcare in Sweden." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-1619.

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<p>Sweden healthcare adopted much ICT (information and communication technology). It is a highly information intensive place. This thesis gives a brief description of the background of healthcare in Sweden and ICT adoption in healthcare, introduces an Information system security model, describes the technology and law about data privacy and carries out a case through questionnaire and interview.</p>
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