Bachelor's Thesis Gabit Sagindykov

This thesis explores the growing necessity for Selective Disclosure (SD) in digital identity systems, particularly within the framework of Self-Sovereign Identity (SSI). SSI shifts control over identity data to the user, promoting privacy, decentralization, and trust. However, SD adds a vital layer by enabling users to disclose only specific attributes of their identity when necessary, minimizing the exposure of personal information. 

Through a comprehensive feature matrix, mechanisms are evaluated based on their suitability for modern identity ecosystems, with a focus on privacy, scalability, and computational efficiency. A prototype integration of the selected SD mechanism demonstrates the practical challenges and benefits of implementing SD in decentralized identity systems. This work provides insights into the current landscape of SD technologies, guiding the choice of effective, user-centered identity solutions in increasingly decentralized environments.