Survey on relational database watermarking techniques

Digital watermarking has been in multimedia data use over the past years. Recently it has become applicable in relational database system not only to secure copyright ownership but also to ensure data contents integrity. Further, it is used in locating tampered and modified places. However, the watermarking relational database has its own requirements, challenges, attacks and limitations. This paper, surveys recent database watermarking techniques focusing on the importance of watermarking relational database, the difference between watermarking relational database and multimedia objects, the issues in watermarking relational database, type of attacks on watermarked database, classifications, distortion introduced and the embedded information. The comparative study shows that watermarking relational database can be an effective tool for copyright protection, tampered detection, and hacker tracing while maintaining the integrity of data contents. In addition, this study explores the current issues in watermarking relational database as well as the significant differences between watermarking multimedia data and relational database contents. Finally, it provides a classification of database watermarking techniques according to the way of selecting the candidate key attributes and tuples, distortion introduced and decoding methods used

Cyber Security

This open access book constitutes the refereed proceedings of the 17th International Annual Conference on Cyber Security, CNCERT 2021, held in Beijing, China, in AJuly 2021. The 14 papers presented were carefully reviewed and selected from 51 submissions. The papers are organized according to the following topical sections: ​data security; privacy protection; anomaly detection; traffic analysis; social network security; vulnerability detection; text classification

Cyber Security

This open access book constitutes the refereed proceedings of the 17th International Annual Conference on Cyber Security, CNCERT 2021, held in Beijing, China, in AJuly 2021. The 14 papers presented were carefully reviewed and selected from 51 submissions. The papers are organized according to the following topical sections: ​data security; privacy protection; anomaly detection; traffic analysis; social network security; vulnerability detection; text classification

Rights Protection for Relational Data Using Least Significant Bit Method

A solution for computer database content rights protection through watermarking. Rights protection for relative information is of ever-increasing interest, particularly considering areas wherever sensitive, valuable content is to be outsourced. A decent example could be a data processing application, wherever, information is sold in items to parties specialized in mining it. Totally different avenues are on the market, every with its own benefits and disadvantages. Social control by legal suggests that is sometimes ineffective in preventing thievery of proprietary works, unless increased by a digital counterpart, for instance, watermarking. Whereas, having the ability to handle higher level linguistics constraints, like classification preservation, our resolution additionally addresses necessary attacks, like set choice and random and linear information changes. We introduce wmdb.*, a proof-of-concept implementation and its application to real-life information, namely, in watermarking the outsourced Wal-Mart sales information that we have on the market at our institute