| Title | Reversible Database Watermarking Based on Random Forest and Genetic Algorithm |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Ge, Chonghui, Sun, Jian, Sun, Yuxin, Di, Yunlong, Zhu, Yongjin, Xie, Linfeng, Zhang, Yingzhou |
| Conference Name | 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) |
| Date Published | Oct. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-8448-7 |
| Keywords | composability, copyright protection, distortion, genetic algorithm, genetic algorithms, Histogram Shifting, Histograms, Human Behavior, Metrics, Prediction algorithms, pubcrawl, Random Forest, relational database security, resilience, Resiliency, reversible watermarking, Robustness, usability, Watermarking |
| Abstract | The advancing information technology is playing more and more important role in data mining of relational database.1 The transfer and sharing of databases cause the copyright-related security threats. Database watermarking technology can effectively solve the problem with copyright protection and traceability, which has been attracting researchers' attention. In this paper, we proposed a novel, robust and reversible database watermarking technique, named histogram shifting watermarking based on random forest and genetic algorithm (RF-GAHCSW). It greatly improves the watermark capacity by means of histogram width reduction and eliminates the impact of the prediction error attack. Meanwhile, random forest algorithm is used to select important attributes for watermark embedding, and genetic algorithm is employed to find the optimal secret key for the database grouping and determine the position of watermark embedding to improve the watermark capacity and reduce data distortion. The experimental results show that the robustness of RF-GAHCSW is greatly improved, compared with the original HSW, and the distortion has little effect on the usability of database. |
| URL | https://ieeexplore.ieee.org/document/9329398 |
| DOI | 10.1109/CyberC49757.2020.00045 |
| Citation Key | ge_reversible_2020 |
Reversible Database Watermarking Based on Random Forest and Genetic Algorithm