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DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and shareIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 SOS SOCIAL SECURITY NUMBER WATCH PROJECT This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles” MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and shareIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 SOS SOCIAL SECURITY NUMBER WATCH PROJECT This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles” MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
RESEARCH PROJECTS AT THE DATA PRIVACY LAB Research in the Data Privacy Lab can best be described through projects that characterize our contributions. Often a single work in the Lab will impact more than oneIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SOS SOCIAL SECURITY NUMBER WATCH PROJECT, FAQ In general, as more digits are provided, more information is reported. Given a full 9-digit Social Security Number, the "full" validation option of the SSNwatch Validation Server identifies: If only the first 3 digits of an SSN are provided, the SSNwatch Validation Server identifies only the state issued. If the first 5 MAINTAINING PATIENT CONFIDENTIALITY WHEN SHARING MEDICAL 4 970202 4973251 n 970202 7321785 y 970202 8324820 n 970203 2018492 n 970203 9353481 y 970203 3856592 n Table 1. Possibly anonymous HIV testdata.
PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . ADAPTIVE GAUSSIAN PROCESS FOR SHORT-TERM WIND SPEED h1 h3 h* hc X1 X2 X* Xc Locality P1 P2 P3 P* Pc Gaussian fields Observations h'1 h'3 h'* h'c X 1 X 2 X * X c Locality P 1 P 2 P 3 P * P c Gaussian fields Observations P* P * Figure3: AGP illustration: it trains separate Gaussian Processes on the Knearest neighbors of each target P, denoted as localityP(preserving the original distance metric), and directly obtains regression boundary. PATIENT-CENTERED MANAGEMENT OF COMPLEX PATIENTS CAN REDUCE Patient-centered Management VOL. 13, NO. 2 THE AMERICAN JOURNAL OF MANAGED CARE 85 Prior work showed that patterns of hospice use byolder Medicare
DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and shareIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 SOS SOCIAL SECURITY NUMBER WATCH PROJECT This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles” MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and shareIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 SOS SOCIAL SECURITY NUMBER WATCH PROJECT This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles” MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
RESEARCH PROJECTS AT THE DATA PRIVACY LAB Research in the Data Privacy Lab can best be described through projects that characterize our contributions. Often a single work in the Lab will impact more than oneIDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SOS SOCIAL SECURITY NUMBER WATCH PROJECT, FAQ In general, as more digits are provided, more information is reported. Given a full 9-digit Social Security Number, the "full" validation option of the SSNwatch Validation Server identifies: If only the first 3 digits of an SSN are provided, the SSNwatch Validation Server identifies only the state issued. If the first 5 MAINTAINING PATIENT CONFIDENTIALITY WHEN SHARING MEDICAL 4 970202 4973251 n 970202 7321785 y 970202 8324820 n 970203 2018492 n 970203 9353481 y 970203 3856592 n Table 1. Possibly anonymous HIV testdata.
PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. PATIENT IDENTIFIABILITY IN PHARMACEUTICAL MARKETING DATA 1. Introduction Price Waterhouse Coopers predicts that sharing personal health information beyond the direct care of the patient will be a two billion dollar market over the next few years . ADAPTIVE GAUSSIAN PROCESS FOR SHORT-TERM WIND SPEED h1 h3 h* hc X1 X2 X* Xc Locality P1 P2 P3 P* Pc Gaussian fields Observations h'1 h'3 h'* h'c X 1 X 2 X * X c Locality P 1 P 2 P 3 P * P c Gaussian fields Observations P* P * Figure3: AGP illustration: it trains separate Gaussian Processes on the Knearest neighbors of each target P, denoted as localityP(preserving the original distance metric), and directly obtains regression boundary. PATIENT-CENTERED MANAGEMENT OF COMPLEX PATIENTS CAN REDUCE Patient-centered Management VOL. 13, NO. 2 THE AMERICAN JOURNAL OF MANAGED CARE 85 Prior work showed that patterns of hospice use byolder Medicare
DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and share SOS SOCIAL SECURITY NUMBER WATCH PROJECTSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATION IRSSOCIAL SECURITY VERIFICATIONSOCIAL SECURITY VERIFICATION ONLINESOCIAL SECURITY VERIFICATION SYSTEM This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. -ANONYMITY: A MODEL FOR PROTECTING PRIVACY1 L. Sweeney. k-anonymity: a model for protecting privacy.International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,10 (5),2002; 557-570.
POEMS WRITTEN BY LATANYA SWEENEY Poems Written by Latanya Sweeney. The Fat Cat That Sat. There was a cat. Her name was Zat. She was called, the fat cat that sat. She sat on hats. She sat on mats. She even sat on other cats. GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles”DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and share SOS SOCIAL SECURITY NUMBER WATCH PROJECTSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATION IRSSOCIAL SECURITY VERIFICATIONSOCIAL SECURITY VERIFICATION ONLINESOCIAL SECURITY VERIFICATION SYSTEM This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. -ANONYMITY: A MODEL FOR PROTECTING PRIVACY1 L. Sweeney. k-anonymity: a model for protecting privacy.International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,10 (5),2002; 557-570.
POEMS WRITTEN BY LATANYA SWEENEY Poems Written by Latanya Sweeney. The Fat Cat That Sat. There was a cat. Her name was Zat. She was called, the fat cat that sat. She sat on hats. She sat on mats. She even sat on other cats. GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles”IDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of DATA PRIVACY COURSE, SYLLABUS Syllabus, Assignments and Grading. About this area The overall objective of the line of research and practice encouraged by this work is to create architectural, algorithmic and technological foundations for the maintenance of the privacy of individuals, the confidentiality of organizations, and the protection of sensitive information, despite the requirement that information be released DR. LATANYA SWEENEY'S HOME PAGE Dr. Latanya Sweeney's Home Page. As Professor of Government and Technology in Residence at Harvard University, my mission is create and use technology to assess and solve societal, political and governance problems, and to teach others how to do the same. On focus area is the scientific study of technology's impact on humankind, andI am the
TALKS ON TECHNOLOGY SCIENCE (TOTS) AND TOPICS IN PRIVACY Spring 2017. This is the schedule of weekly talks on Technology Science from expert researchers, public interest groups, and others on the social impact of technology and its unforseen consequences.. Join us on most Friday mornings 10:30 AM - 12 PM at CGIS Knafel, MODEL-BASED FACE DE-IDENTIFICATION R.Gross, L.Sweeney, F.de la Torre, S.Baker. Model-Based Face De-Identification. IEEE Workshop on Privacy Research in Vision, 2006 Model-Based Face De-Identification DEMONSTRATION OF A PRIVACY-PRESERVING SYSTEM THAT PERFORMS Sweeney, L. Demonstration of a Privacy-Preserving System that Performs an Unduplicated Accounting of Services across Homeless Programs.U.S. Government Release October MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
INFORMATION REVELATION AND PRIVACY IN ONLINE SOCIAL NETWORKS R. Gross and A.Acquisti. Information Revelation and Privacy in Online Social Networks. Workshop on Privacy in the Electronic Society (WPES),2005
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL The final result should look similar to the example shown below. From the equation for that straight line (y = 19.486x - 0.002) we can conclude that the best IDENTIFYING PARTICIPANTS IN THE PERSONAL GENOME PROJECT BY Sweeney, Abu and Winn Identifying Participants in the Personal Genome Project by Name 2 (e.g., from 23andMe), but these services oftenDATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and share SOS SOCIAL SECURITY NUMBER WATCH PROJECTSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATION IRSSOCIAL SECURITY VERIFICATIONSOCIAL SECURITY VERIFICATION ONLINESOCIAL SECURITY VERIFICATION SYSTEM This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. -ANONYMITY: A MODEL FOR PROTECTING PRIVACY1 L. Sweeney. k-anonymity: a model for protecting privacy.International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,10 (5),2002; 557-570.
POEMS WRITTEN BY LATANYA SWEENEY Poems Written by Latanya Sweeney. The Fat Cat That Sat. There was a cat. Her name was Zat. She was called, the fat cat that sat. She sat on hats. She sat on mats. She even sat on other cats. GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles”DATA PRIVACY LAB
The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and share SOS SOCIAL SECURITY NUMBER WATCH PROJECTSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATIONSOCIAL SECURITY NUMBER VERIFICATION IRSSOCIAL SECURITY VERIFICATIONSOCIAL SECURITY VERIFICATION ONLINESOCIAL SECURITY VERIFICATION SYSTEM This is an academic demonstration and not fit for any purpose beyond our educational use. NEITHER HARVARD UNIVERSITY NOR ANY INDIVIDUAL OR ENTITY ASSOCIATED WITH THIS PROJECT MAKES ANY WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED, STATUATORY OR OTHERWISE, INCLUDING WITHOUT LIMITATION WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PRIVACY-PRESERVING SURVEILLANCE PROJECT Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. Work in the Data Privacy Lab on SELECTIVE REVELATION Privacy-Preserving Surveillance Using Selective Revelation by Latanya Sweeney. Abstract. Following the events of September 11, 2001, many inthe American public
SIMPLE DEMOGRAPHICS OFTEN IDENTIFY PEOPLE UNIQUELY L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. Sweeney Page 2 PRESERVING PRIVACY BY DE-IDENTIFYING FACIAL IMAGES E.Newton,L.Sweeney,andB.Malin.Preserving Privacy by De-identifying Facial Images, Carnegie Mellon University, School of Computer Science, Technical Report, CMU-CS-03-119. -ANONYMITY: A MODEL FOR PROTECTING PRIVACY1 L. Sweeney. k-anonymity: a model for protecting privacy.International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,10 (5),2002; 557-570.
POEMS WRITTEN BY LATANYA SWEENEY Poems Written by Latanya Sweeney. The Fat Cat That Sat. There was a cat. Her name was Zat. She was called, the fat cat that sat. She sat on hats. She sat on mats. She even sat on other cats. GUARANTEEING ANONYMITY WHEN SHARING MEDICAL DATA, THE Guaranteeing Anonymity when Sharing Medical Data, the Datafly System Latanya Sweeney Clinical Decision Making Group Laboratory for ComputerScience
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL E. Next step is to add axis labels and legend to the graph. Select “Layout” tab from “Chart Tools”. Then add a header using the “Chart Title” button and add axis labels using “Axis Titles”IDENTIFIABILITY
Simple Demographics Often Identify People Uniquely by Latanya Sweeney In this document, I report on experiments I conducted using 1990 U.S. Census summary data to determine how many individuals within geographically situated populations had combinations of DATA PRIVACY COURSE, SYLLABUS Syllabus, Assignments and Grading. About this area The overall objective of the line of research and practice encouraged by this work is to create architectural, algorithmic and technological foundations for the maintenance of the privacy of individuals, the confidentiality of organizations, and the protection of sensitive information, despite the requirement that information be released DR. LATANYA SWEENEY'S HOME PAGE Dr. Latanya Sweeney's Home Page. As Professor of Government and Technology in Residence at Harvard University, my mission is create and use technology to assess and solve societal, political and governance problems, and to teach others how to do the same. On focus area is the scientific study of technology's impact on humankind, andI am the
TALKS ON TECHNOLOGY SCIENCE (TOTS) AND TOPICS IN PRIVACY Spring 2017. This is the schedule of weekly talks on Technology Science from expert researchers, public interest groups, and others on the social impact of technology and its unforseen consequences.. Join us on most Friday mornings 10:30 AM - 12 PM at CGIS Knafel, MODEL-BASED FACE DE-IDENTIFICATION R.Gross, L.Sweeney, F.de la Torre, S.Baker. Model-Based Face De-Identification. IEEE Workshop on Privacy Research in Vision, 2006 Model-Based Face De-Identification DEMONSTRATION OF A PRIVACY-PRESERVING SYSTEM THAT PERFORMS Sweeney, L. Demonstration of a Privacy-Preserving System that Performs an Unduplicated Accounting of Services across Homeless Programs.U.S. Government Release October MATCHING KNOWN PATIENTS TO HEALTH RECORDS IN WASHINGTON Sweeney Matching Known Patients to Health Records in Washington StateData
INFORMATION REVELATION AND PRIVACY IN ONLINE SOCIAL NETWORKS R. Gross and A.Acquisti. Information Revelation and Privacy in Online Social Networks. Workshop on Privacy in the Electronic Society (WPES),2005
HOW TO MAKE A STRAIGHT LINE FIT USING EXCEL The final result should look similar to the example shown below. From the equation for that straight line (y = 19.486x - 0.002) we can conclude that the best IDENTIFYING PARTICIPANTS IN THE PERSONAL GENOME PROJECT BY Sweeney, Abu and Winn Identifying Participants in the Personal Genome Project by Name 2 (e.g., from 23andMe), but these services oftenProjects
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theDataMap
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_Preserve a web page as it appears today._ ------------------------- The Data Privacy Lab is dedicated to creating technologies and related policies with guarantees of privacy protection while allowing society to collect and share private (or sensitive) information for many worthy purposes. We do this by partnering with institutions, agencies, and corporations facing real-world privacy concerns. The Data Privacy Lab seeks balanced, integrated solutions that weave technology andpolicy together.
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