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As open science principles continue to gain traction, striking a balance between patient privacy and data accessibility has become more crucial in medical research than ever before. Encryption-based pseudonymization is a powerful tool to ensure compliance with data protection regulations from both local institutional guidelines and broader regional regulations, such as the General Data Protection Regulation of the European Union. Employing this type of pseudonymization protects the privacy and security of research participants, and allows researchers to effortlessly comply with data security regulations. The pseudonymization workflow however, can vary significantly across research projects, limiting the usability of supporting software tools. Here we present ALIIAS, a customizable pseudonymization framework that allows easy and flexible deployment of custom pseudonymization software, dedicated to the specific ethical and experimental requirements of individual research projects. Features include compatibility with hardware security tokens paired with two-factor authentication, integration to the survey web application LimeSurvey, as well as custom-format pseudonyms and automatic barcode generation. Collectively, these features make ALIIAS suitable for integration into various research infrastructures and lower the initial barrier to incorporating cutting-edge encryption-based pseudonymization in translational and clinical research practices.