基于哈希算法的企业内部文档访问日志脱敏方法OA

In the face of massive and high-speed access logs,the computational efficiency of some computationally intensive traditional data desensitizing methods becomes a bottleneck,indirectly affecting the balance between data pri-vacy protection and data utility.The article proposes a method for desensitizing enterprise's internal document access logs based on hash algorithm.The access logs are visualized as tuple form,and the identifier attribute is introduced in the K-anonymity privacy algorithm;the sensitive attributes of the access logs within the tuples are divided,and the cat-egory label list is output.Using the output list as the range of field attributes to be desensitized,an innovative fusion of one-way hash algorithm and random salt addition strategy is used for log access generalization desensitization.The out-put fixed length string replaces the sensitive attribute information in the original log,achieving efficient and reliable de-sensitization of log data.The experimental results show that when the number of concurrent thread requests is 1 500,the design method only takes an average of 125.36 ms to complete batch log desensitization.After using the design method for desensitization,the success rate of injection attacks is 0.42%,which can effectively resist 99.58%of re-identification attempts,demonstrating the strong application stability and security reliability of the design method.