Abstract
Edge storage is driven by the emerging edge computing and application intelligence, which makes the data anonymization become essential to guarantee the security of the data. The risk with data anonymization is that it can be re-identified, where anonoymized data is matched with available information to discover the individual. Appropriate data anonymization techniques can help on reducing the risk of re-identification. It is very challenging to protect data privacy against re-identification attacks without significantly reduce usefulness of the data. This work proposes an evaluation framework for data anonymization techniques to measure the risks of re-identification and usefulness of anonymized data.