Disclosure Risk and Disclosure Avoidance for Microdata
Bibliographic Data
| ID | 19418368 |
|---|---|
| Authors | Gerhard Paass (Fraunhofer Institute for Applied Information Technology, corresponding author) |
| Year | 1988 |
| Volume | 6 |
| Issue | 4 |
| Pages | 487-500 |
| Publication date | 1988-10-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.1988.10509697 |
| OpenAlex | W2168459699 |
| Language | EN |
| Citations received | 5 |
| References cited | 6 |
Under given concrete exogenous conditions, the fraction of identifiable records in a microdata file without positive identifiers such as name and address is estimated. The effect of possible noise in the data, as well as the sample property of microdata files, is taken into account. Using real microdata files, it is shown that there is no risk of disclosure if the information content of characteristics known to the investigator (additional knowledge) is limited. Files with additional knowledge of large information content yield a high risk of disclosure. This can be eliminated only by massive modifications of the data records, which, however, involve large biases for complex statistical evaluations. In this case, the requirement for privacy protection and high-quality data perhaps may be fulfilled only if the linkage of such files with extensive additional knowledge is prevented by appropriate organizational and legal restrictions
Actuarial science · Business · Data quality · Identifier · Information retrieval · Internet privacy · Population · Record linkage · Unique identifier · Computer Science · Data Quality and Management · Data-Driven Disease Surveillance · Medicine · Privacy-Preserving Technologies in Data · Marketing
| Citations per year | 0.14 |
|---|---|
| Citation span | 1989 - 2011 (23) |
| Highly cited | No |