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Statements

Subject Item
dbr:Privacy
dbo:wikiPageWikiLink
dbr:Data_re-identification
Subject Item
dbr:De-anonymization
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데이터 재식별화 Data re-identification
rdfs:comment
Data re-identification or de-anonymization is the practice of matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the individual to which the data belong. This is a concern because companies with privacy policies, health care providers, and financial institutions may release the data they collect after the data has gone through the de-identification process. 데이터 재식별화(data re-identification, 再識別化), 비익명화(de-anonymization)는 ('비식별화된 데이터')를 데이터에 속한 개인을 식별하기 위해 이미 공개된 정보나 보조 데이터와 일치시키는 과정이다. 이것은 개인정보를 다루는 기관, 의료 제공자, 금융 기관이 데이터가 비식별화 과정을 거친 이후 수집된 데이터를 공개할 수 있다는 우려가 있다. 비식별화 과정은 직간접 식별자의 마스킹, 일반화, 삭제를 수반한다. 그러나 이러한 과정에 보편적인 정의는 존재하지 않는다. 퍼블릭 도메인 내 정보는 심지어는 익명화되어 보이더라도 사용 가능한 다른 데이터와 기초적인 컴퓨터 과학 기법을 조합하여 재식별화가 가능하다. 더욱 더 많은 데이터가 인터넷에 공개되고 있다. 이 데이터는 출처의 개인정보 보호를 보장하기 위해 이름, 주소, 주민등록번호 등의 개인 식별 정보(PII)를 제거하는 등 일부 기법을 거쳐 공개된다. 이러한 보장은 정부가 합법적으로 제안된 데이터 집합을 별도의 권한을 요구하지 않고도 타사와 공유할 수 있게 해준다. 이러한 데이터는 연구원들, 특히 의료 분야 연구원들에게 매우 가치가 있는 것으로 입증되고 있다.
rdfs:seeAlso
dbr:Accountability_Act dbr:Family_Educational_Rights dbr:Health_Insurance_Portability dbr:Privacy_Act
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dbc:Information_governance dbc:Privacy dbc:Internet_privacy dbc:Anonymity
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dbo:abstract
Data re-identification or de-anonymization is the practice of matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the individual to which the data belong. This is a concern because companies with privacy policies, health care providers, and financial institutions may release the data they collect after the data has gone through the de-identification process. The de-identification process involves masking, generalizing or deleting both direct and indirect identifiers; the definition of this process is not universal. Information in the public domain, even seemingly anonymized, may thus be re-identified in combination with other pieces of available data and basic computer science techniques. The Protection of Human Subjects ('Common Rule#Signatories'), a collection of multiple U.S. federal agencies and departments including the U.S. Department of Health and Human Services, speculate that re-identification is becoming gradually easier because of "big data"—the abundance and constant collection and analysis of information along the evolution of technologies and the advances of algorithms. However, others have claimed that de-identification is a safe and effective data liberation tool and do not view re-identification as a concern. More and more data are becoming publicly available over the Internet. These data are released after applying some anonymization techniques like removing personally identifiable information (PII) such as names, addresses and social security numbers to ensure the sources' privacy. This assurance of privacy allows the government to legally share limited data sets with third parties without requiring written permission. Such data has proved to be very valuable for researchers, particularly in health care. The risk of re-identification is significantly reduced with GDPR-compliant pseudonymization which requires that data cannot be attributed to a specific data subject without the use of separately kept "additional information". GDPR compliant pseudonymized data embodies the state of the art in Data Protection by Design and by Default because it requires protection of both direct and indirect identifiers (not just direct). GDPR Data Protection by Design and by Default principles as embodied in pseudonymization require protection of both direct and indirect identifiers so that personal data is not cross-referenceable (or re-identifiable) via the Mosaic Effect without access to "additional information" that is kept separately by the controller. Because access to separately kept "additional information" is required for re-identification, attribution of data to a specific data subject can be limited by the controller to support lawful purposes only. 데이터 재식별화(data re-identification, 再識別化), 비익명화(de-anonymization)는 ('비식별화된 데이터')를 데이터에 속한 개인을 식별하기 위해 이미 공개된 정보나 보조 데이터와 일치시키는 과정이다. 이것은 개인정보를 다루는 기관, 의료 제공자, 금융 기관이 데이터가 비식별화 과정을 거친 이후 수집된 데이터를 공개할 수 있다는 우려가 있다. 비식별화 과정은 직간접 식별자의 마스킹, 일반화, 삭제를 수반한다. 그러나 이러한 과정에 보편적인 정의는 존재하지 않는다. 퍼블릭 도메인 내 정보는 심지어는 익명화되어 보이더라도 사용 가능한 다른 데이터와 기초적인 컴퓨터 과학 기법을 조합하여 재식별화가 가능하다. 더욱 더 많은 데이터가 인터넷에 공개되고 있다. 이 데이터는 출처의 개인정보 보호를 보장하기 위해 이름, 주소, 주민등록번호 등의 개인 식별 정보(PII)를 제거하는 등 일부 기법을 거쳐 공개된다. 이러한 보장은 정부가 합법적으로 제안된 데이터 집합을 별도의 권한을 요구하지 않고도 타사와 공유할 수 있게 해준다. 이러한 데이터는 연구원들, 특히 의료 분야 연구원들에게 매우 가치가 있는 것으로 입증되고 있다.
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