A New Mining and Protection Method Based on Sensitive Data

Abstract EN

The traditional method of sensitive data identification for data stream has a large amount of calculation and does not reflect the impact of time on the data value, and the mining accuracy is not high.

In view of the above problems we firstly adopt the sliding window mechanism to divide the data flow according to time and delay the dataset according to the characteristics of the data flow in the sliding window to achieve the purpose of saving time and space.

At the same time, threshold sensitivity analysis is used to find out the optimal threshold.

Finally, a K-anonymous algorithm based on dynamic rounding function is employed to achieve the protection of sensitive data.

Theoretical analysis and experimental results show that the algorithm can effectively mine the sensitive data in the data stream and can effectively protect the sensitive data.