Abstract
In the big data era, privacy preserving is a vital security challenge for data mining. Common object of privacy preserving is personal privacy, which should be kept unrevealed while data mining on group information. However, for a few sensitive groups, such as suffering from some particular disease, engaging in some special occupation or having some peculiar hobby, even if every personal data is processed for privacy preserving, group specificity can be still exposed. Therefore, we propose the concept and method of anti-data mining on group privacy information. By adding, swapping data according to our rules, the minable characteristic and group specificity of original data is destroyed and eliminated to prevent group privacy from data mining.
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Acknowledgement
The project was supported by the National Natural Science Foundation of China under Grant 61502440 and the Open Research Project of The Hubei Key Laboratory of Intelligent Geo-Information Processing under Grant KLIGIP1610.
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Yang, F., Tian, T., Yao, H., Zhao, X., Zheng, T., Ning, M. (2018). Anti-data Mining on Group Privacy Information. In: Zu, Q., Hu, B. (eds) Human Centered Computing. HCC 2017. Lecture Notes in Computer Science(), vol 10745. Springer, Cham. https://doi.org/10.1007/978-3-319-74521-3_51
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DOI: https://doi.org/10.1007/978-3-319-74521-3_51
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