Anonymization of Sensitive Data through Cryptography

Abstract: In today's interconnected digital landscape, the protection of sensitive information is of great importance. As a result, the field of cryptography plays a vital role in ensuring individuals' anonymity and data integrity. In this context, this thesis presents a comprehensive analysis of symmetric encryption algorithms, specifically focusing on the Advanced Encryption Standard (AES) and Camellia. By investigating the performance aspects of these algorithms, including encryption time, decryption time, and ciphertext size, the goal is to provide valuable insights for selecting suitable cryptographic solutions. The findings indicate that while there is a difference in performance between the algorithms, the disparity is not substantial in practical terms. Both AES and Camellia, as well as their larger key-size alternatives, demonstrated comparable performance, with AES128 showing marginally faster encryption time. The study's implementation also involves encrypting a data set with sensitive information on students. It encrypts the school classes with separate keys and assigns roles to users, enabling access control based on user roles. The implemented solution successfully addressed the problem of role-based access control and encryption of unique identifiers, as verified through the verification and validation method. The implications of this study extend to industries and society, where cryptography plays a vital role in protecting individuals' anonymity and data integrity. The results presented in this paper can serve as a valuable reference for selecting suitable cryptographic algorithms for various systems and applications, particularly for anonymization of usernames or short, unique identifiers. However, it is important to note that the experiment primarily focused on small data sets, and further investigations may yield different results for larger data sets.