A T-similarity Sensitive Information Protection Method Based on Sensitive Information Gradient Partition
Linping Su, Zhipeng Liu · Journal of Physics Conference Series · 2021
Nowadays, data technology has been widely used. Researchers have also made an in-depth exploration on how to effectively protect sensitive information in massive data, including k-anonymity, l-diversity and t-similarity. In this paper, the main ideas of the three technologies are described, and the characteristics of the three technologies are analyzed. By introducing the concept of sensitive gradient when calculating the similarity distance, the defect of not being sensitive to the sensitive attribute value in t-similarity technology is improved and supplemented. Algorithm for t-similarity technology can form more effective protection for sensitive attribute values with high privacy requirements under acceptable time overhead differences, and can meet the needs of practical applications.