Data-driven Anonymization Process Applied to Time Series
نویسندگان
چکیده
Digital transformation and Big Data allow the use of highly valuable data. However, these data can be individual or sensitive, and represent an obvious threat for privacy. Anonymization, which achieves a trade-off between data protection and data utility, can be used in this context. There is not global anonymization technique which fits at all applications. Here, we describe a data-driven anonymization process and apply it on simulated electrical load data.
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تاریخ انتشار 2017