RELATIONAL DATA WATERMARKING: FUNDAMENTALS

This course provides essential content and skills that directly support the Ph.D. program in Computer Science. It is designed to equip students with the theoretical and practical foundations of information hiding and watermarking, with a particular focus on protecting relational databases.
The objectives of this course are to analyze, apply, and extend watermarking architectures for relational databases, with particular emphasis on the AHK algorithm as a foundation for developing advanced watermarking techniques. To achieve these goals, students will examine the fundamental properties and requirements of digital watermarking and explore the adversary model of this data protection approach.
Achieving these objectives enables students to design data protection solutions without restricting access to or distribution of the data, thereby significantly expanding its potential applications.

At the end of this course, the students will be able to:
- Identify when it is more convenient to apply watermarking techniques to protect digital assets, rather than considering other security methods.
- Understand the advantages and risks of applying watermarking techniques for ownership protection and data tampering detection, among other applications.
- Know the particularities and convenience of applying fragile vs. robust watermarking.
- Design and implement a watermarking technique based on the watermarking trade-off management, proposing variations of the main architecture.

Among the main prerequisites of the course, it is required:
- The capacity to understand (read and listen) the content presented in English and the ability to communicate (write and speak) using this language.
- To know the basics of set theory, linear algebra, and mathematical logic, as basics for the design and programming of algorithms.
Note: Although a basic understanding of relational database theory is desirable, this is not mandatory for students, considering a brief introduction to this topic is included in the course.

1. Introduction to digital watermarking
2. Basic watermarking architecture
3. Types of assets and carriers
4. Lab. Protection based on the type of digital asset
5. The Agrawal & Kiernan (AHK) algorithm
6. Lab. Development of a simple watermarking scheme
7. Watermark properties and requirements
8. Lab. Implementation of watermark properties
9. The adversary model
10. Lab. Basic robustness strategies

- Agrawal, R., & Kiernan, J. (2002, January). Watermarking relational databases. In VLDB'02: Proceedings of the 28th International Conference on Very Large Databases (pp. 155-166). Morgan Kaufmann.
- Halder, R., Pal, S., & Cortesi, A. (2010). Watermarking techniques for relational databases: Survey, classification and comparison. Journal of universal computer science, 16(21), 3164-3190.
- Rani, S., & Halder, R. (2022). Comparative analysis of relational database watermarking techniques: An empirical study. IEEE Access, 10, 27970-27989.
- Cox, I., Miller, M., Bloom, J., Fridrich, J., and Kalker, I., Digital Watermarking and Steganography. Morgan kaufmann, 2007.
- Barni, M. and Bartolini, F., 2004. Watermarking systems engineering: enabling digital assets security and other applications. Crc Press.

The main evaluation of the course takes place after all the content has been covered. It consists of a 45-minute written exam in the form of a test, including matching questions, true/false items, completion tasks, and others. The exam is designed to assess the student’s ability to identify the most appropriate solutions for situations that may threaten the integrity or authorship of a relational database.
The exam will include both theoretical and practical questions, addressing the fundamental concepts of digital watermarking along with their requirements, characteristics, and classification criteria.
During the exam, the use of printed materials (such as books, articles, or class notes) is not permitted. The use of cell phones or other electronic devices, including tablets and laptops, is also prohibited.
In addition to the written exam, students will be evaluated on their performance in labs and lessons. This performance will serve as an individual criterion considered in the professor’s final assessment. Thus, while the written exam constitutes the main evaluation, student performance throughout the course also contributes to the overall assessment, which, together with the exam, determines the final grade.
The maximum score for the written exam is 25 out of 30. The remaining 5 points are awarded based on the student’s individual performance.
To encourage student participation and learning, each lesson will include examples followed by questions, with evaluation exercises conducted first collectively and then individually. This approach allows any doubts regarding the evaluation process to be clarified in advance.
In addition to the exercises reviewed in class, students have access to supplementary materials on the university’s e-learning platform, moodle.unive.it.

written

Regarding the grading scale, scores will be assigned according to the following scheme:
A. Scores in the 18–22 range will be awarded when the student demonstrates sufficient knowledge of the content delivered in class and an adequate ability to analyze and investigate watermarking methods for relational databases.
B. Scores in the 23–26 range will be awarded in the presence of a fair knowledge of the content taught in class, as well as a satisfactory performance in the analysis and investigation of watermarking methods for relational databases, and the ability to consider solutions related to other disciplines or security methods.
C. Scores in the 27–30 range will be awarded in the presence of good or excellent knowledge of the content offered in the lessons and strong analytical and investigative skills regarding the security concepts and methods presented in the cases. At this level, the student must demonstrate greater independence in conducting research, as well as a high ability to analyze and integrate watermarking methods with other solutions or disciplines.
D. “Cum laude” will be awarded in the presence of excellent knowledge of the content and outstanding performance in participation and implementation of solutions discussed in class.

This in-person course incorporates structured learning modules available on the university’s online learning platform, moodle.unive.it. These modules host materials considered essential to the course and serve as a reference for students throughout their studies. They are designed to engage students in solving real-world practical cases, fostering critical thinking and problem-solving skills. Additionally, the platform allows students to compare their solutions with those proposed by the instructor or applied in professional practice, thereby reinforcing understanding and promoting the integration of theoretical knowledge with practical application.

This subject deals with topics related to the macro-area "Cities, infrastructure and social capital" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development