A statistical characteristics preserving watermarking scheme for time series databases
Database watermarking is one of the most effective methods to protect the copyright of databases.However,tra-ditional database watermarking has a potential drawback:watermark embedding will change the distribution of data,which may affect the use and analysis of databases.Considering that most analyses are based on the statistical characteristics of the target database,keeping the consistency of the statistical characteristics is the key to ensuring analyzability.Since stat-istical characteristics analysis is performed in groups,compared with traditional relational databases,time series databases(TSDBs)have obvious time-grouping characteristics and are more valuable for analysis.Therefore,this paper proposes a robust watermarking algorithm for time series databases,effectively ensuring the consistency of statistical characteristics.Based on the time-group characteristics of TSDBs,we propose a three-step watermarking method,which is based on lin-ear regression,error compensation,and watermark verification,named RCV.According to the properties of the linear re-gression model and error compensation,the proposed watermark method generates a series of data that have the same stat-istical characteristics.Then,the verification mechanism is performed to validate the generated data until it conveys the tar-get watermark message.Compared with the existing methods,our method achieves superior robustness and preserves con-stant statistical properties better.
database watermarkingtime series databasestatistical characteristicstime-group characteristics
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