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随着云计算、物联网和社交媒体技术的快速发展,大数据挖掘和分析成为未来知识发现的重要手段,数据隐私泄露问题日趋严重,如何保护用户隐私和防止敏感信息泄露成为面临的最大挑战。由于大数据具有规模大、多样性、动态更新速度快等特点,许多传统的隐私保护技术不再适用。文章从知识发现的视角,总结了隐私保护数据挖掘的生命周期模型;从输入隐私和输出隐私方面对隐私保护数据挖掘的相关技术研究进行了分类评述;最后,对隐私保护数据挖掘的研究挑战和未来展望进行了阐述。
Abstract：With the rapid development of cloud computing, Internet of Things and social media technologies, big data mining and analysis have become an important means of knowledge discovery in the future. The content of information with personal privacy is becoming more and more diverse, and the problem of data privacy leakage is becoming increasingly serious. How to protect user privacy and prevent sensitive information leakage has become the biggest challenge. Because of the large scale, diversity, and fast dynamic update of big data, many traditional privacy preserving technologies are no longer applicable. This article summarizes the life cycle model of privacy preserving data mining from the perspective of knowledge discovery. The related research on privacy preserving data mining is classified and reviewed in terms of input privacy and output privacy. The research challenges and future prospects of privacy preserving data mining are described.
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基本信息:
中图分类号:TP309;TP311.13
引用信息:
[1]杨洋,陈红军.隐私保护数据挖掘技术研究综述[J].微型电脑应用,2020,36(08):41-44+54.
基金信息:
北京市教育委员会社科计划一般项目(SQSM201714073001)
2020-08-20
2020-08-20