Project / 06
ITA-Maskit
A local data-masking tool with deterministic pseudonymization, a desktop GUI, and explicit processing boundaries for large tabular data.
The problem to solve
Data masking often involves sensitive material, so processing boundaries and repeatability matter. ITA-Maskit focuses on local processing, deterministic pseudonymization, and a desktop GUI so the masking flow runs on the local machine.
My design and implementation
I organized the flow around local processing, used deterministic pseudonymization to preserve replacement relationships for the same input, and provided a GUI as the operating surface. The README reports 1M-row benchmarks and a test count.
System architecture
The system consists of a local processing path, pseudonymization logic, desktop GUI, and input/output boundaries. Material enters the flow on the local machine, while the GUI handles operation and feedback; “local” is not expanded into an additional compliance claim here.
Key technical decisions
Local processing makes the data boundary explicit; deterministic pseudonymization keeps replacement relationships repeatable; and the GUI exposes processing steps to desktop users. These decisions correspond to capabilities reported by the README.
Results and validation evidence
The README reports local processing, deterministic pseudonymization, a GUI, 1M-row benchmarks, and a test count. This section preserves that benchmark and test evidence without adding a masking-quality or security-certification claim.
Known limitations and next steps
The README-reported benchmark and test count are not presented as a guarantee across every data shape. A next step is to cover more input boundaries while preserving the local-processing and deterministic-pseudonymization semantics and recording the resulting validation.