Data Anonymization: K-anonymity Sensitivity Analysis
Title | Data Anonymization: K-anonymity Sensitivity Analysis |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Santos, W., Sousa, G., Prata, P., Ferrão, M. E. |
Conference Name | 2020 15th Iberian Conference on Information Systems and Technologies (CISTI) |
Date Published | June 2020 |
Publisher | IEEE |
ISBN Number | 978-989-54659-0-3 |
Keywords | anonymity, ARX, ARX k-anonymization, Brazilian higher education evaluation system, central governments, composability, data anonimization, data anonymization, data privacy, data protection, data usability, digitization process, Education, European General Data Protection Regulation, further education, GDPR, government data processing, Human Behavior, k-anonymity, k-anonymity sensitivity analysis, local authorities, Metrics, open government data, personal data privacy, personal data protection, pubcrawl, resilience, Resiliency, sensitivity analysis, social justice, Sociology, Statistics, Tools |
Abstract | These days the digitization process is everywhere, spreading also across central governments and local authorities. It is hoped that, using open government data for scientific research purposes, the public good and social justice might be enhanced. Taking into account the European General Data Protection Regulation recently adopted, the big challenge in Portugal and other European countries, is how to provide the right balance between personal data privacy and data value for research. This work presents a sensitivity study of data anonymization procedure applied to a real open government data available from the Brazilian higher education evaluation system. The ARX k-anonymization algorithm, with and without generalization of some research value variables, was performed. The analysis of the amount of data / information lost and the risk of re-identification suggest that the anonymization process may lead to the under-representation of minorities and sociodemographic disadvantaged groups. It will enable scientists to improve the balance among risk, data usability, and contributions for the public good policies and practices. |
URL | https://ieeexplore.ieee.org/document/9141044 |
DOI | 10.23919/CISTI49556.2020.9141044 |
Citation Key | santos_data_2020 |
- pubcrawl
- Human behavior
- k-anonymity
- k-anonymity sensitivity analysis
- local authorities
- Metrics
- open government data
- personal data privacy
- personal data protection
- government data processing
- resilience
- Resiliency
- sensitivity analysis
- Social Justice
- Sociology
- Statistics
- tools
- anonymity
- GDPR
- further education
- European General Data Protection Regulation
- education
- digitization process
- data usability
- Data protection
- data privacy
- data anonymization
- data anonimization
- composability
- central governments
- Brazilian higher education evaluation system
- ARX k-anonymization
- ARX