摘要
为了避免数据的共享与交换可能造成的个人隐私泄露问题,基于随机干扰技术设计了一种针对文本型数据的隐私保护方法,可以为具有单个敏感属性或多个相关联敏感属性的数据提供隐私保护服务,有效解决了传统的随机干扰方法不适用于文本类型数据的问题。该方法通过进行文本语义的扩展,使得被干扰后的数据与原数据在语义上保持最大程度的接近,从而实现了在进行隐私保护的同时,确保数据质量。实验结果表明,该方法具有较好的隐私保护效果。
In order to avoid personal privacy disclosure in the data sharing and exchange process,a privacy protection method for text data is designed based on random jamming technique,which can provide privacy protection for data with a single sensitive attribute or multiple associated sensitive attributes.This method effectively solves the problem that the traditional data jamming method is not suitable for text data.By extending the text semantics,this method can keep the disturbed data close to the original data to the greatest extent semantically,thus ensuring the data quality while achieving privacy protection.Experimental results show that this method has good privacy protection effect.
作者
徐雅斌
郭昊
XU Yabin;GUO Hao(Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,Beijing 100101,China;Beijing Advanced Innovation Center for Materials Genome Engineering,Beijing Information Science and Technology University,Beijing 100101,China;School of Computer,Beijing Information Science&Technology University,Beijing 100101,China)
出处
《北京信息科技大学学报（自然科学版）》
2021年第1期51-56,共6页
Journal of Beijing Information Science and Technology University
基金
网络文化与数字传播北京市重点实验室资助项目(ICDDXN004)
信息网络安全公安部重点实验室开放课题资助项目(C18601)。
