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You searched for subject:( Statistical Privacy). Showing records 1 – 16 of 16 total matches.

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Princeton University

1. Liu, Changchang. Rethinking the Science of Statistical Privacy .

Degree: PhD, 2019, Princeton University

 Nowadays, more and more data, such as social network data, mobility data, business data, medical data, are shared or made public to enable real world… (more)

Subjects/Keywords: Auxiliary Information; Differential Privacy; Statistical Privacy

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APA (6th Edition):

Liu, C. (2019). Rethinking the Science of Statistical Privacy . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp017d278w81g

Chicago Manual of Style (16th Edition):

Liu, Changchang. “Rethinking the Science of Statistical Privacy .” 2019. Doctoral Dissertation, Princeton University. Accessed July 20, 2019. http://arks.princeton.edu/ark:/88435/dsp017d278w81g.

MLA Handbook (7th Edition):

Liu, Changchang. “Rethinking the Science of Statistical Privacy .” 2019. Web. 20 Jul 2019.

Vancouver:

Liu C. Rethinking the Science of Statistical Privacy . [Internet] [Doctoral dissertation]. Princeton University; 2019. [cited 2019 Jul 20]. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w81g.

Council of Science Editors:

Liu C. Rethinking the Science of Statistical Privacy . [Doctoral Dissertation]. Princeton University; 2019. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w81g


University of Manchester

2. Liu, Meng-Chang. Achieving privacy-preserving distributed statistical computation.

Degree: PhD, 2012, University of Manchester

 The growth of the Internet has opened up tremendous opportunities for cooperative computations where the results depend on the private data inputs of distributed participating… (more)

Subjects/Keywords: 004.678; Data Privacy; Privacy-preserving Distributed Statistical Computation; Privacy-preserving Two-party Sign Test Computation

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APA (6th Edition):

Liu, M. (2012). Achieving privacy-preserving distributed statistical computation. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558058

Chicago Manual of Style (16th Edition):

Liu, Meng-Chang. “Achieving privacy-preserving distributed statistical computation.” 2012. Doctoral Dissertation, University of Manchester. Accessed July 20, 2019. https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558058.

MLA Handbook (7th Edition):

Liu, Meng-Chang. “Achieving privacy-preserving distributed statistical computation.” 2012. Web. 20 Jul 2019.

Vancouver:

Liu M. Achieving privacy-preserving distributed statistical computation. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2019 Jul 20]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558058.

Council of Science Editors:

Liu M. Achieving privacy-preserving distributed statistical computation. [Doctoral Dissertation]. University of Manchester; 2012. Available from: https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558058


University of Newcastle

3. Giggins, Helen. Security of genetic databases.

Degree: PhD, 2009, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

The rapid pace of growth in the field of human genetics has left researchers with many new challenges… (more)

Subjects/Keywords: statistical disclosure control; trust; privacy; security; genetic databases; statistical databases

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APA (6th Edition):

Giggins, H. (2009). Security of genetic databases. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/35251

Chicago Manual of Style (16th Edition):

Giggins, Helen. “Security of genetic databases.” 2009. Doctoral Dissertation, University of Newcastle. Accessed July 20, 2019. http://hdl.handle.net/1959.13/35251.

MLA Handbook (7th Edition):

Giggins, Helen. “Security of genetic databases.” 2009. Web. 20 Jul 2019.

Vancouver:

Giggins H. Security of genetic databases. [Internet] [Doctoral dissertation]. University of Newcastle; 2009. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/1959.13/35251.

Council of Science Editors:

Giggins H. Security of genetic databases. [Doctoral Dissertation]. University of Newcastle; 2009. Available from: http://hdl.handle.net/1959.13/35251


Penn State University

4. Snoke, Joshua. STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES.

Degree: 2018, Penn State University

 In this dissertation, we develop statistical methods for providing access to sensitive data, with the goal of simultaneously protecting individuals privacy and enabling high quality… (more)

Subjects/Keywords: Statistical Data Privacy; Disclosure Control; Multiparty Computation; Differential Privacy; Partitioned Data; Synthetic Data

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APA (6th Edition):

Snoke, J. (2018). STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES. (Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/15621jvs140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Snoke, Joshua. “STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES.” 2018. Thesis, Penn State University. Accessed July 20, 2019. https://etda.libraries.psu.edu/catalog/15621jvs140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Snoke, Joshua. “STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES.” 2018. Web. 20 Jul 2019.

Vancouver:

Snoke J. STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES. [Internet] [Thesis]. Penn State University; 2018. [cited 2019 Jul 20]. Available from: https://etda.libraries.psu.edu/catalog/15621jvs140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Snoke J. STATISTICAL DATA PRIVACY METHODS FOR INCREASING RESEARCH OPPORTUNITIES. [Thesis]. Penn State University; 2018. Available from: https://etda.libraries.psu.edu/catalog/15621jvs140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Hong Kong University of Science and Technology

5. Kellaris, Georgios. Practical differential privacy.

Degree: 2015, Hong Kong University of Science and Technology

 In this thesis we focus on publishing statistics on a private database with ϵ-differential privacy. We target at three scenarios; (i) when the statistics are… (more)

Subjects/Keywords: Electronic data processing; Statistical methods; Mathematical models; Privacy

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APA (6th Edition):

Kellaris, G. (2015). Practical differential privacy. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1514471 ; http://repository.ust.hk/ir/bitstream/1783.1-78843/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kellaris, Georgios. “Practical differential privacy.” 2015. Thesis, Hong Kong University of Science and Technology. Accessed July 20, 2019. https://doi.org/10.14711/thesis-b1514471 ; http://repository.ust.hk/ir/bitstream/1783.1-78843/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kellaris, Georgios. “Practical differential privacy.” 2015. Web. 20 Jul 2019.

Vancouver:

Kellaris G. Practical differential privacy. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2015. [cited 2019 Jul 20]. Available from: https://doi.org/10.14711/thesis-b1514471 ; http://repository.ust.hk/ir/bitstream/1783.1-78843/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kellaris G. Practical differential privacy. [Thesis]. Hong Kong University of Science and Technology; 2015. Available from: https://doi.org/10.14711/thesis-b1514471 ; http://repository.ust.hk/ir/bitstream/1783.1-78843/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

6. Kairouz, Peter. The fundamental limits of statistical data privacy.

Degree: PhD, Electrical & Computer Engr, 2016, University of Illinois – Urbana-Champaign

 The Internet is shaping our daily lives. On the one hand, social networks like Facebook and Twitter allow people to share their precious moments and… (more)

Subjects/Keywords: Privacy; Information Theory; Data Privacy; Statistics; Multi-Party Computation; Security; Local Differential Privacy; Privacy-Preserving Machine Learning Algorithms; Information Theoretic Utilities; f-Divergence; Mutual Information; Statistical Inference; Hypothesis Testing; Estimation

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APA (6th Edition):

Kairouz, P. (2016). The fundamental limits of statistical data privacy. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/92686

Chicago Manual of Style (16th Edition):

Kairouz, Peter. “The fundamental limits of statistical data privacy.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed July 20, 2019. http://hdl.handle.net/2142/92686.

MLA Handbook (7th Edition):

Kairouz, Peter. “The fundamental limits of statistical data privacy.” 2016. Web. 20 Jul 2019.

Vancouver:

Kairouz P. The fundamental limits of statistical data privacy. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2142/92686.

Council of Science Editors:

Kairouz P. The fundamental limits of statistical data privacy. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/92686


University of Newcastle

7. King, Tatiana. Privacy issues in health care and security of statistical databases.

Degree: PhD, 2008, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

Privacy of personal information is becoming a major problem in health care, in the light of coming implementation… (more)

Subjects/Keywords: medical research; privacy; privacy protection; statistical databases; public's attitude towards privacy; health care

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APA (6th Edition):

King, T. (2008). Privacy issues in health care and security of statistical databases. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/803191

Chicago Manual of Style (16th Edition):

King, Tatiana. “Privacy issues in health care and security of statistical databases.” 2008. Doctoral Dissertation, University of Newcastle. Accessed July 20, 2019. http://hdl.handle.net/1959.13/803191.

MLA Handbook (7th Edition):

King, Tatiana. “Privacy issues in health care and security of statistical databases.” 2008. Web. 20 Jul 2019.

Vancouver:

King T. Privacy issues in health care and security of statistical databases. [Internet] [Doctoral dissertation]. University of Newcastle; 2008. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/1959.13/803191.

Council of Science Editors:

King T. Privacy issues in health care and security of statistical databases. [Doctoral Dissertation]. University of Newcastle; 2008. Available from: http://hdl.handle.net/1959.13/803191


University of California – Berkeley

8. Sankararaman, Sriram. Statistical models for analyzing human genetic variation.

Degree: Computer Science, 2010, University of California – Berkeley

 Advances in sequencing and genomic technologies are providing new opportunities to understand the genetic basis of phenotypes such as diseases. Translating the large volumes of… (more)

Subjects/Keywords: Computer Science; Statistics; Biology, Bioinformatics; Functional residue prediction; Genomic privacy; Human genetic variation; Statistical models

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APA (6th Edition):

Sankararaman, S. (2010). Statistical models for analyzing human genetic variation. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/8j30h6p8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sankararaman, Sriram. “Statistical models for analyzing human genetic variation.” 2010. Thesis, University of California – Berkeley. Accessed July 20, 2019. http://www.escholarship.org/uc/item/8j30h6p8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sankararaman, Sriram. “Statistical models for analyzing human genetic variation.” 2010. Web. 20 Jul 2019.

Vancouver:

Sankararaman S. Statistical models for analyzing human genetic variation. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2019 Jul 20]. Available from: http://www.escholarship.org/uc/item/8j30h6p8.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sankararaman S. Statistical models for analyzing human genetic variation. [Thesis]. University of California – Berkeley; 2010. Available from: http://www.escholarship.org/uc/item/8j30h6p8

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Pretoria

9. Zielinski, Marek Piotr. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation.

Degree: Computer Science, 2010, University of Pretoria

Statistical data, such as in the form of microdata, is used by different organisations as a basis for creating knowledge to assist in their planning… (more)

Subjects/Keywords: Statistical databases; Information security; Microdata; Confidentiality; Microaggregation; Global recoding; Economic price theory; Optimum balance; Information utility; Privacy; UCTD

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APA (6th Edition):

Zielinski, M. (2010). On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation. (Doctoral Dissertation). University of Pretoria. Retrieved from http://hdl.handle.net/2263/25371

Chicago Manual of Style (16th Edition):

Zielinski, Marek. “On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation.” 2010. Doctoral Dissertation, University of Pretoria. Accessed July 20, 2019. http://hdl.handle.net/2263/25371.

MLA Handbook (7th Edition):

Zielinski, Marek. “On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation.” 2010. Web. 20 Jul 2019.

Vancouver:

Zielinski M. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation. [Internet] [Doctoral dissertation]. University of Pretoria; 2010. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2263/25371.

Council of Science Editors:

Zielinski M. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation. [Doctoral Dissertation]. University of Pretoria; 2010. Available from: http://hdl.handle.net/2263/25371


University of Pretoria

10. [No author]. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation .

Degree: 2010, University of Pretoria

Statistical data, such as in the form of microdata, is used by different organisations as a basis for creating knowledge to assist in their planning… (more)

Subjects/Keywords: Statistical databases; Information security; Microdata; Confidentiality; Microaggregation; Global recoding; Economic price theory; Optimum balance; Information utility; Privacy; UCTD

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APA (6th Edition):

author], [. (2010). On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation . (Doctoral Dissertation). University of Pretoria. Retrieved from http://upetd.up.ac.za/thesis/available/etd-06092010-182948/

Chicago Manual of Style (16th Edition):

author], [No. “On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation .” 2010. Doctoral Dissertation, University of Pretoria. Accessed July 20, 2019. http://upetd.up.ac.za/thesis/available/etd-06092010-182948/.

MLA Handbook (7th Edition):

author], [No. “On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation .” 2010. Web. 20 Jul 2019.

Vancouver:

author] [. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation . [Internet] [Doctoral dissertation]. University of Pretoria; 2010. [cited 2019 Jul 20]. Available from: http://upetd.up.ac.za/thesis/available/etd-06092010-182948/.

Council of Science Editors:

author] [. On the use of economic price theory to determine the optimum levels of privacy and information utility in microdata anonymisation . [Doctoral Dissertation]. University of Pretoria; 2010. Available from: http://upetd.up.ac.za/thesis/available/etd-06092010-182948/

11. Liu, Meng-Chang. Achieving Privacy-preserving Distributed Statistical Computation.

Degree: 2012, University of Manchester

 The growth of the Internet has opened up tremendous opportunities for cooperative computations where the results depend on the private data inputs of distributed participating… (more)

Subjects/Keywords: Data Privacy; Privacy-preserving Distributed Statistical Computation; Privacy-preserving Two-party Sign Test Computation

…of Philosophy Thesis Title: Achieving Privacy-preserving Distributed Statistical… …transformation methodology has also been demonstrated; it includes data privacy definition, statistical… …Distributed Statistical Computation Distributed statistical computation, however, raises privacy… …practical solution to the privacy-preserving distributed statistical computation (PPDSC)… …approach incorporates privacy definition, statistical algorithm decomposition, solution design… 

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APA (6th Edition):

Liu, M. (2012). Achieving Privacy-preserving Distributed Statistical Computation. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:166980

Chicago Manual of Style (16th Edition):

Liu, Meng-Chang. “Achieving Privacy-preserving Distributed Statistical Computation.” 2012. Doctoral Dissertation, University of Manchester. Accessed July 20, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:166980.

MLA Handbook (7th Edition):

Liu, Meng-Chang. “Achieving Privacy-preserving Distributed Statistical Computation.” 2012. Web. 20 Jul 2019.

Vancouver:

Liu M. Achieving Privacy-preserving Distributed Statistical Computation. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2019 Jul 20]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:166980.

Council of Science Editors:

Liu M. Achieving Privacy-preserving Distributed Statistical Computation. [Doctoral Dissertation]. University of Manchester; 2012. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:166980


Wright State University

12. Kim, Dae Wook. Data-Driven Network-Centric Threat Assessment.

Degree: PhD, Computer Science and Engineering PhD, 2017, Wright State University

 As the Internet has grown increasingly popular as a communication and information sharing platform, it has given rise to two major types of Internet security… (more)

Subjects/Keywords: Computer Science; network security; fake anti-virus software; intrusion detection; web document analysis; statistical classification; Domain Name System; behavioral fingerprints; privacy; online social networks; virtual currency; malicious accounts

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APA (6th Edition):

Kim, D. W. (2017). Data-Driven Network-Centric Threat Assessment. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1495191891086814

Chicago Manual of Style (16th Edition):

Kim, Dae Wook. “Data-Driven Network-Centric Threat Assessment.” 2017. Doctoral Dissertation, Wright State University. Accessed July 20, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495191891086814.

MLA Handbook (7th Edition):

Kim, Dae Wook. “Data-Driven Network-Centric Threat Assessment.” 2017. Web. 20 Jul 2019.

Vancouver:

Kim DW. Data-Driven Network-Centric Threat Assessment. [Internet] [Doctoral dissertation]. Wright State University; 2017. [cited 2019 Jul 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1495191891086814.

Council of Science Editors:

Kim DW. Data-Driven Network-Centric Threat Assessment. [Doctoral Dissertation]. Wright State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1495191891086814


Vanderbilt University

13. Yin, Zhijun. Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text.

Degree: PhD, Computer Science, 2018, Vanderbilt University

 Traditional methods for collecting data in support of clinical research include prospectively collected surveys, retrospective analyses of existing medical records, and a combination of the… (more)

Subjects/Keywords: Hormonal Therapy; Data Mining; Machine Learning; Statistical Inference; Natural Language Processing; Treatment Adherence; User Generated Content; Health Behavior; Patient Portal; Privacy; Social Media; Online Health Community

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APA (6th Edition):

Yin, Z. (2018). Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-02112018-221351/ ;

Chicago Manual of Style (16th Edition):

Yin, Zhijun. “Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed July 20, 2019. http://etd.library.vanderbilt.edu/available/etd-02112018-221351/ ;.

MLA Handbook (7th Edition):

Yin, Zhijun. “Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text.” 2018. Web. 20 Jul 2019.

Vancouver:

Yin Z. Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2019 Jul 20]. Available from: http://etd.library.vanderbilt.edu/available/etd-02112018-221351/ ;.

Council of Science Editors:

Yin Z. Automated Learning Of Health Behaviors Through Consumer Authored Natural Language Text. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://etd.library.vanderbilt.edu/available/etd-02112018-221351/ ;

14. Kamm, Liina. Privacy-preserving statistical analysis using secure multi-party computation .

Degree: 2015, Tartu University

 Kaasaegses ühiskonnas luuakse inimese kohta digitaalne kirje kohe pärast tema sündi. Sellest hetkest alates jälgitakse tema käitumist ning kogutakse andmeid erinevate eluvaldkondade kohta. Kui kasutate… (more)

Subjects/Keywords: statistiline analüüs; konfidentsiaalne info; privaatsus; Sharemind (tarkvara); confidential information; statistical analysis; privacy; Sharemind (software)

…the author’s contribution to privacy preserving statistical analysis methods, and their… …Willemson, J.: Privacy-preserving statistical data analysis on federated databases. In… …privacy preserving statistical analysis but is not included in this thesis. This report has not… …statistical studies in the privacy-preserving setting using the secure multi-party computation… …in the privacy-preserving setting. We implement four most frequently used statistical tests… 

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APA (6th Edition):

Kamm, L. (2015). Privacy-preserving statistical analysis using secure multi-party computation . (Thesis). Tartu University. Retrieved from http://hdl.handle.net/10062/45343

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kamm, Liina. “Privacy-preserving statistical analysis using secure multi-party computation .” 2015. Thesis, Tartu University. Accessed July 20, 2019. http://hdl.handle.net/10062/45343.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kamm, Liina. “Privacy-preserving statistical analysis using secure multi-party computation .” 2015. Web. 20 Jul 2019.

Vancouver:

Kamm L. Privacy-preserving statistical analysis using secure multi-party computation . [Internet] [Thesis]. Tartu University; 2015. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/10062/45343.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kamm L. Privacy-preserving statistical analysis using secure multi-party computation . [Thesis]. Tartu University; 2015. Available from: http://hdl.handle.net/10062/45343

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universitetet i Tromsø

15. Hailemichael, Meskerem Asfaw. Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data .

Degree: 2015, Universitetet i Tromsø

 Motivation: Despite its enormous benefits, EHR data reuse is limited because of multi-dimensional challenges where privacy comes on the forefront. Recently various privacy-preserving statistical computation… (more)

Subjects/Keywords: VDP::Medical disciplines: 700::Health sciences: 800; VDP::Medisinske Fag: 700::Helsefag: 800; Computation Graph; Data reuse; EHR; Health Information System; Health Research; Privacy; Statistical Computing; Secure Multi-party Computation; Secure Summation; Virtual Dataset

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hailemichael, M. A. (2015). Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data . (Masters Thesis). Universitetet i Tromsø. Retrieved from http://hdl.handle.net/10037/9154

Chicago Manual of Style (16th Edition):

Hailemichael, Meskerem Asfaw. “Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data .” 2015. Masters Thesis, Universitetet i Tromsø. Accessed July 20, 2019. http://hdl.handle.net/10037/9154.

MLA Handbook (7th Edition):

Hailemichael, Meskerem Asfaw. “Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data .” 2015. Web. 20 Jul 2019.

Vancouver:

Hailemichael MA. Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data . [Internet] [Masters thesis]. Universitetet i Tromsø 2015. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/10037/9154.

Council of Science Editors:

Hailemichael MA. Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data . [Masters Thesis]. Universitetet i Tromsø 2015. Available from: http://hdl.handle.net/10037/9154


McGill University

16. Arès, Sébastien. Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne.

Degree: Master of Laws, Institute of Comparative Law., 2005, McGill University

Data matching is the automated process permitting the comparison of significant amounts of personal data from two or more different databanks in order to produce… (more)

Subjects/Keywords: Statistical matching; Data protection  – Law and legislation  – Canada; Privacy, Right of  – Canada; Public records  – Access control  – Canada; Public records  – Law and legislation  – Canada; Canada. Canadian Charter of Rights and Freedoms.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Arès, S. (2005). Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne. (Masters Thesis). McGill University. Retrieved from http://digitool.library.mcgill.ca/thesisfile82651.pdf

Chicago Manual of Style (16th Edition):

Arès, Sébastien. “Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne.” 2005. Masters Thesis, McGill University. Accessed July 20, 2019. http://digitool.library.mcgill.ca/thesisfile82651.pdf.

MLA Handbook (7th Edition):

Arès, Sébastien. “Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne.” 2005. Web. 20 Jul 2019.

Vancouver:

Arès S. Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne. [Internet] [Masters thesis]. McGill University; 2005. [cited 2019 Jul 20]. Available from: http://digitool.library.mcgill.ca/thesisfile82651.pdf.

Council of Science Editors:

Arès S. Le couplage de données et la protection de la vie privée informationnelle sous l'article 8 de la Charte canadienne. [Masters Thesis]. McGill University; 2005. Available from: http://digitool.library.mcgill.ca/thesisfile82651.pdf

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