Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked...Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.展开更多
A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. ...A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.展开更多
基金supported by the National Key Research and Development Program of China under Grant 2021YFB2700600the National Natural Science Foundation of China under Grant 62132013 and 61902292+1 种基金the Key Research and Development Programs of Shaanxi under Grants 2021ZDLGY06-03the Truth-Seeking Research Scholarship Fund of Xidian University。
文摘Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.
基金Supported by the Aeronautics Science Foundation of China (02F52033), the High-Technology Research Project of Jiangsu Province (BG2004005) and Youth Research Foundation of Qufu Normal Univer-sity(XJ02057)
文摘A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.