{"title":"最小失真:关系数据的高容量水印技术","authors":"M. L. P. Gort, C. F. Uribe, J. Nummenmaa","doi":"10.1145/3082031.3083241","DOIUrl":null,"url":null,"abstract":"In this paper, a new multi-attribute and high capacity image-based watermarking technique for relational data is proposed. The embedding process causes low distortion into the data considering the usability restrictions defined over the marked relation. The conducted experiments show the high resilience of the proposed technique against tuple deletion and tuple addition attacks. An interesting trend of the extracted watermark is analyzed when, within certain limits, if the number of embedded marks is small, the watermark signal far from being compromised, discretely improves in the case of tuple addition attacks. According to the results, marking 13% of the attributes and under an attack of 100% of tuples addition, 96% of the watermark is extracted. Also, while previous techniques embed up to 61% of the watermark, under the same conditions, we guarantee to embed 99.96% of the marks.","PeriodicalId":431672,"journal":{"name":"Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A Minimum Distortion: High Capacity Watermarking Technique for Relational Data\",\"authors\":\"M. L. P. Gort, C. F. Uribe, J. Nummenmaa\",\"doi\":\"10.1145/3082031.3083241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new multi-attribute and high capacity image-based watermarking technique for relational data is proposed. The embedding process causes low distortion into the data considering the usability restrictions defined over the marked relation. The conducted experiments show the high resilience of the proposed technique against tuple deletion and tuple addition attacks. An interesting trend of the extracted watermark is analyzed when, within certain limits, if the number of embedded marks is small, the watermark signal far from being compromised, discretely improves in the case of tuple addition attacks. According to the results, marking 13% of the attributes and under an attack of 100% of tuples addition, 96% of the watermark is extracted. Also, while previous techniques embed up to 61% of the watermark, under the same conditions, we guarantee to embed 99.96% of the marks.\",\"PeriodicalId\":431672,\"journal\":{\"name\":\"Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3082031.3083241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3082031.3083241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Minimum Distortion: High Capacity Watermarking Technique for Relational Data
In this paper, a new multi-attribute and high capacity image-based watermarking technique for relational data is proposed. The embedding process causes low distortion into the data considering the usability restrictions defined over the marked relation. The conducted experiments show the high resilience of the proposed technique against tuple deletion and tuple addition attacks. An interesting trend of the extracted watermark is analyzed when, within certain limits, if the number of embedded marks is small, the watermark signal far from being compromised, discretely improves in the case of tuple addition attacks. According to the results, marking 13% of the attributes and under an attack of 100% of tuples addition, 96% of the watermark is extracted. Also, while previous techniques embed up to 61% of the watermark, under the same conditions, we guarantee to embed 99.96% of the marks.