A new secure arrangement for privacy-preserving data collection

A big number of users' healthy data are necessary for the Internet of Things (IoT) healthcare. Therefore, the institutions, which have access to more data can provide better medical services such as more accurate diagnosis. However, privacy is often a bottleneck for IoT healthcare. Users often refuse to provide their health data based on privacy considerations. To balance the requirement of data collection and personal privacy, a lot of privacy preserving data collection schemes are provided. A very important work of these schemes is to produce a secret position for every user to store her/his data, which is named secure arrangement. A novel secure arrangement method is proposed in this paper, which is based on matrix eigenvalue calculation. Compared with the current secure arrangement methods, the proposed method is more robust and efficient, which drives the proposed scheme to be more suitable for repeated aggregation. Then we use an example to illustrate how to use the proposed arrangement method to construct a privacy data collection protocol. We prove the proposed scheme is secure and efficient in security analysis and efficiency analysis.

Automated summary

User health data is essential for IoT healthcare, but privacy is often a challenge. Many privacy-preserving data collection schemes have been proposed to balance the need for data collection and personal privacy. The proposed secure arrangement method based on matrix eigenvalue calculation is more robust and efficient compared to current methods.