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Freedom of privacy: Anonymous data collection with respondent-defined privacy protection

机译：隐私自由：具有响应者定义的隐私保护的匿名数据收集

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摘要

Respondents face many types of privacy threats when submitting their personal information to an agency on the Internet. This provides the agency access to their personal identifiable information (PII) such as IP addresses, which it obtains from the points of origin of the messages. Anyone who accesses the agency's database also comes to know the PII, where by the privacy of the respondents is compromised. The respondents must make sure of the agency's ability to protect their privacy in advance before responding to surveys. Hence, there is a clear need for methods that allow responses to be gathered in a way that protects the privacy of the participants. A micro-data vector (MDV can be grouped into two general categories, namely, quasi-identifiers and sensitive information. The quasi-identifiers which are available in any publicly available database (such as a voter list), can be used to partially identify individuals. Sensitive information (salary for example) is meant to be restricted to the individuals and they may not wish to be publicly identified with it. A model is proposed for data protection to ensure respondent privacy protection.
机译：在将个人信息提交给Internet上的代理机构时，受访者面临多种类型的隐私威胁。这使代理机构可以访问其个人身份信息（PII），例如IP地址，这些信息是从消息的原始点获得的。任何访问该机构数据库的人都会知道PII，在此PII会损害受访者的隐私。受访者在回应调查之前必须事先确保该机构保护其隐私的能力。因此，显然需要允许以保护参与者的隐私的方式来收集响应的方法。微数据矢量（MDV可以分为两大类，即准标识符和敏感信息。在任何公共可用数据库（例如投票者列表）中可用的准标识符可用于部分识别个人：敏感信息（例如，薪水）仅限于个人，他们可能不希望与个人公开识别个人身份；为此，提出了一种数据保护模型以确保响应者的隐私保护。

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  • 来源
    《Operations Research》 |2012年第2期|p.137-138|共2页
  • 作者

    Rajeev Kumar; Ram Copal; Robert Garfinkel;

  • 作者单位

    Department of Accounting and Finance, Kutztown University, Kutztown, PA 19530;

    Department of Operations and Information Management,University of Connecticut, Storrs, CT 06269;

    Department of Operations and Information Management,University of Connecticut, Storrs, CT 06269;

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