Na Ren , Yuchen Hu , Changqing Zhu , Shuitao Guo , Xianshu Zhu
{"title":"Moment invariants based zero watermarking algorithm for trajectory data","authors":"Na Ren , Yuchen Hu , Changqing Zhu , Shuitao Guo , Xianshu Zhu","doi":"10.1016/j.jisa.2024.103867","DOIUrl":null,"url":null,"abstract":"<div><p>Zero watermarking is a lossless copyright protection technology that satisfies the need for copyright protection without compromising the accuracy of trajectory data. However, existing zero watermarking algorithms for trajectory data are unable to resist random deletion point attack. Therefore, a trajectory data zero watermarking algorithm based on moment invariants was proposed to address the problem. Firstly, two compression algorithms are utilized to extract feature points from the trajectory data. Then, a coordinate system is constructed using the minimum area bounding rectangle (MABR) of the feature points. Next, based on the constructed coordinate system, the feature points are divided into subtrajectories, and the linear moment invariants generated by the subtrajectories are calculated. Finally, the zero watermark information is constructed based on the linear moment invariants, and the watermark copyright information is generated by exclusive-ORing (XOR) it with the copyright image. Experimental results demonstrate that the zero watermark information constructed by the proposed algorithm has good uniqueness and strong robustness against random deletion, compression, and other common attacks. Furthermore, the proposed algorithm has good algorithm efficiency and is applicable to vector data with plane coordinates. The study makes a positive contribution to copyright protection for trajectory data and provides useful references for research on lossless watermarking of vector geographic data.</p></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"86 ","pages":"Article 103867"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Security and Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214212624001698","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Zero watermarking is a lossless copyright protection technology that satisfies the need for copyright protection without compromising the accuracy of trajectory data. However, existing zero watermarking algorithms for trajectory data are unable to resist random deletion point attack. Therefore, a trajectory data zero watermarking algorithm based on moment invariants was proposed to address the problem. Firstly, two compression algorithms are utilized to extract feature points from the trajectory data. Then, a coordinate system is constructed using the minimum area bounding rectangle (MABR) of the feature points. Next, based on the constructed coordinate system, the feature points are divided into subtrajectories, and the linear moment invariants generated by the subtrajectories are calculated. Finally, the zero watermark information is constructed based on the linear moment invariants, and the watermark copyright information is generated by exclusive-ORing (XOR) it with the copyright image. Experimental results demonstrate that the zero watermark information constructed by the proposed algorithm has good uniqueness and strong robustness against random deletion, compression, and other common attacks. Furthermore, the proposed algorithm has good algorithm efficiency and is applicable to vector data with plane coordinates. The study makes a positive contribution to copyright protection for trajectory data and provides useful references for research on lossless watermarking of vector geographic data.
期刊介绍:
Journal of Information Security and Applications (JISA) focuses on the original research and practice-driven applications with relevance to information security and applications. JISA provides a common linkage between a vibrant scientific and research community and industry professionals by offering a clear view on modern problems and challenges in information security, as well as identifying promising scientific and "best-practice" solutions. JISA issues offer a balance between original research work and innovative industrial approaches by internationally renowned information security experts and researchers.