一种基于用户行为模式的匿名数据鉴定方法

An Anonymous Data Authentication Method Based on User Behavior Pattern

针对匿名用户数据的海量性与冗余性等特点,为提高数字证据的用户身份鉴定性能,文章提出基于用户行为模式的匿名数据鉴定方法。首先,文章研究了基于BIDE算法的用户频繁行为模式挖掘方法,为数据鉴定提供了高质量的用户频繁序列行为模式库。然后,采用基于最长公共子序列的相似度方法得到模式综合相似度,全面描述用户数据之间的吻合程度。最后,分别使用Web浏览数据集和Unix操作命令行数据集进行实验,结果表明,文章所提出的数字证据鉴定方法具有良好的适用性和计算效率,为匿名数据的同一鉴定提供了技术支撑。

Aiming at the characteristics of massive and redundant anonymous user data,in order to improve the performance of user identification based on digital evidence,this paper proposes an anonymous data authentication method based on user behavior pattern.Firstly,this paper studies the mining method of frequent user behavior patterns based on BIDE algorithm,which provides a high-quality user frequent sequence behavior pattern library for data authentication.Then,the similarity method based on the longest common subsequence is used to obtain the comprehensive similarity of patterns,which can comprehensively describe the matching degree between user data.Finally,experiments are carried out using Web browsing data set and Unix operating command line data set.The results show that the proposed digital evidence authentication method has good applicability and computational efficiency,which provides technical support for the same authentication of anonymous data.