关联数据库中抗扰动优化方法研究与仿真

Research and Simulation of Disturbance Resistance Optimization Method in Relational Database

研究数据库抗扰动性优化问题。当前的数据库中的数据形式上以个体存在,数据库相互之间存在关联,造成了一些隐私数据被干扰,对数据库形成扰动。传统的数据库抗扰动方法采用随机噪声对那些秘密属性进行加密,用户访问修改后的数据,虽然增强了数据访问的安全性,但同时也使数据库扰动前属性与扰动后属性的对应关系发生混乱,数据很难恢复到噪声扰动之前的状态,降低了数据库的抗扰动性。提出了一种基于隐私保护的数据库抗扰动优化方法。提取成对约束条件特征,从而获取数据库抗扰动的成对约束条件。根据上述约束条件,进行数据库抗扰动处理,以提高数据库的抗扰动性。实验结果表明,利用改进后的算法进行数据库抗扰动处理,能够极大地提高数据库的抗扰动性,同时保证数据库的隐私性,从而提高数据库的性能。

The anti disturbance optimization problem of database was researched. An improved anti disturbance optimization method of data based was proposed based on a privacy protection. The constraints condition features in pairs were extracted. The pair constraint conditions of database anti disturbance were obtained. The anti disturbance processing of database was taken based on the constraint conditions. The anti disturbance performance of database was improved. Simulation results show that the anti disturbance performance of database can be improved greatly with proposed algorithm, the privacy of the database can be ensured, and the performance of database is improved.