{"title":"新冠肺炎患者隐私保护时空轨迹公布","authors":"N. L. Rajesh, Sajimon Abraham, Shyni S. Das","doi":"10.1080/17489725.2021.1906965","DOIUrl":null,"url":null,"abstract":"ABSTRACT To control the community spread of Covid-19 by health authorities, citizens’ use of contact tracing mobile applications is vital. Publication of these traces for prospective probes, the collected spatio-temporal traces of Covid-19 positive cases through LBS contributes to personal privacy violation. So, the data collector must anonymise the essential attributes in the trajectories before initiating the release of trajectory data. We propose an approach that provides sufficient personal protection to the individuals while publishing their trajectory data by anonymising very sensitive stay locations like home, work-locations, etc. Anonymisation of more locations in trajectories upsets the data utility of Covid-19 traces in future studies. This work creates Haversine distance measured Minimum Bounding Rectangular (MBR) stay zones, over the most sensitive stay locations with similar Places of Interest to provide anonymity and prevents the adversary from getting known the exact information about the sensitive stay locations. Since the published versions of GPS traces of Covid-19 patients were unavailable, we created sample dummy datasets by altering the available spatio-temporal datasets. The result proves that the data utility is a little high, and the information loss is low, but comparable to the other similar methods.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"16 1","pages":"25 - 53"},"PeriodicalIF":1.2000,"publicationDate":"2021-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2021.1906965","citationCount":"0","resultStr":"{\"title\":\"Privacy preserved spatio-temporal trajectory publication of Covid-19 patients\",\"authors\":\"N. L. Rajesh, Sajimon Abraham, Shyni S. Das\",\"doi\":\"10.1080/17489725.2021.1906965\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT To control the community spread of Covid-19 by health authorities, citizens’ use of contact tracing mobile applications is vital. Publication of these traces for prospective probes, the collected spatio-temporal traces of Covid-19 positive cases through LBS contributes to personal privacy violation. So, the data collector must anonymise the essential attributes in the trajectories before initiating the release of trajectory data. We propose an approach that provides sufficient personal protection to the individuals while publishing their trajectory data by anonymising very sensitive stay locations like home, work-locations, etc. Anonymisation of more locations in trajectories upsets the data utility of Covid-19 traces in future studies. This work creates Haversine distance measured Minimum Bounding Rectangular (MBR) stay zones, over the most sensitive stay locations with similar Places of Interest to provide anonymity and prevents the adversary from getting known the exact information about the sensitive stay locations. Since the published versions of GPS traces of Covid-19 patients were unavailable, we created sample dummy datasets by altering the available spatio-temporal datasets. The result proves that the data utility is a little high, and the information loss is low, but comparable to the other similar methods.\",\"PeriodicalId\":44932,\"journal\":{\"name\":\"Journal of Location Based Services\",\"volume\":\"16 1\",\"pages\":\"25 - 53\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2021-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/17489725.2021.1906965\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Location Based Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17489725.2021.1906965\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Location Based Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17489725.2021.1906965","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Privacy preserved spatio-temporal trajectory publication of Covid-19 patients
ABSTRACT To control the community spread of Covid-19 by health authorities, citizens’ use of contact tracing mobile applications is vital. Publication of these traces for prospective probes, the collected spatio-temporal traces of Covid-19 positive cases through LBS contributes to personal privacy violation. So, the data collector must anonymise the essential attributes in the trajectories before initiating the release of trajectory data. We propose an approach that provides sufficient personal protection to the individuals while publishing their trajectory data by anonymising very sensitive stay locations like home, work-locations, etc. Anonymisation of more locations in trajectories upsets the data utility of Covid-19 traces in future studies. This work creates Haversine distance measured Minimum Bounding Rectangular (MBR) stay zones, over the most sensitive stay locations with similar Places of Interest to provide anonymity and prevents the adversary from getting known the exact information about the sensitive stay locations. Since the published versions of GPS traces of Covid-19 patients were unavailable, we created sample dummy datasets by altering the available spatio-temporal datasets. The result proves that the data utility is a little high, and the information loss is low, but comparable to the other similar methods.
期刊介绍:
The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.