{"title":"An empirical study on the robustness of a fragile watermark for relational databases","authors":"I. Kamel, Waheeb Yaqub, K. Kamel","doi":"10.1109/INNOVATIONS.2013.6544423","DOIUrl":null,"url":null,"abstract":"Databases most often contain critical information. Unauthorized changes to databases can have serious consequences and may result in significant losses for the organization. This paper presents a viable solution for protecting the integrity of the data stored in relational databases using fragile watermarking. Prior techniques introduce distortions to the watermarked values and thus cannot be applied to all attributes. Our technique protects relational tables by reordering tuples relative to each other according to a secrete value (watermark). This paper introduces empirical study on the effect of data distribution and other data measures like the mean and standard deviation on the attack detection rates. A study on the cost, in terms of the execution time, of the proposed watermark insertion and data verification algorithms is also presented.","PeriodicalId":438270,"journal":{"name":"2013 9th International Conference on Innovations in Information Technology (IIT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th International Conference on Innovations in Information Technology (IIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INNOVATIONS.2013.6544423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Databases most often contain critical information. Unauthorized changes to databases can have serious consequences and may result in significant losses for the organization. This paper presents a viable solution for protecting the integrity of the data stored in relational databases using fragile watermarking. Prior techniques introduce distortions to the watermarked values and thus cannot be applied to all attributes. Our technique protects relational tables by reordering tuples relative to each other according to a secrete value (watermark). This paper introduces empirical study on the effect of data distribution and other data measures like the mean and standard deviation on the attack detection rates. A study on the cost, in terms of the execution time, of the proposed watermark insertion and data verification algorithms is also presented.