Protecting Personally Identifiable Information (PII) in Critical Infrastructure Data Using Differential Privacy
| Autor: | Rajendra K. Raj, Carol J. Romanowski, Asma Alnemari, Sumita Mishra |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
021110 strategic
defence & security studies Information privacy Emergency management Computer science business.industry Internet privacy 0211 other engineering and technologies Workload 02 engineering and technology Safeguarding Critical infrastructure 020204 information systems Health care 0202 electrical engineering electronic engineering information engineering ComputingMilieux_COMPUTERSANDSOCIETY Differential privacy business Personally identifiable information |
| Zdroj: | 2019 IEEE International Symposium on Technologies for Homeland Security (HST). |
| DOI: | 10.1109/hst47167.2019.9032942 |
| Popis: | In critical infrastructure (CI) sectors such as emergency management or healthcare, researchers can analyze and detect useful patterns in data and help emergency management personnel efficaciously allocate limited resources or detect epidemiology spread patterns. However, all of this data contains personally identifiable information (PII) that needs to be safeguarded for legal and ethical reasons. Traditional techniques for safeguarding, such as anonymization, have shown to be ineffective. Differential privacy is a technique that supports individual privacy while allowing the analysis of datasets for societal benefit. This paper motivates the use of differential privacy to answer a wide range of queries about CI data containing PII with better privacy guarantees than is possible with traditional techniques. Moreover, it introduces a new technique based on Multiple-attribute Workload Partitioning, which does not depend on the nature of the underlying dataset and provides better protection for privacy than current differential privacy approaches. |
| Databáze: | OpenAIRE |
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