About EntrD
EntrD’s Software Solutions: FileFactory & DataFactory
The Importance of Data Masking and Anonymization
Data masking plays a crucial role in transforming sensitive data into a format that’s usable for testing and analysis without compromising privacy. This methodology ensures that sensitive data is shielded from potential unauthorized access while retaining its integrity for practical applications.
The key features of data masking include:
- Protection of Sensitive Data: By replacing real data with fictitious but realistic data, it ensures that sensitive information is not exposed.
- Usability: The masked data remains functional and can be used for development, testing, and training purposes without compromising security.
- Compliance: Helps organizations comply with data protection regulations by ensuring that sensitive data is not used inappropriately.
Document masking
Document masking is the practice of obscuring confidential information within documents to protect individual privacy and minimize risks such as data breaches.
This technique involves replacing sensitive details with fictitious or placeholder data, ensuring compliance with privacy regulations and maintaining the overall structure and usefulness of the documents for collaboration and analysis purposes.
Overcoming Challenges with Innovate Solutions
To address this challenge, EntrD engaged in a strategic partnership with DataNorth AI to enhance their capabilities in data anonymization and document masking.
DataNorth AI created an innovative solution using a large language model (LLM) to improve entity extraction accuracy. This approach involved a multi-step process:
- OCR Technology: Initially, optical character recognition (OCR) technology converts digital document text into machine-readable format.
- Preprocessing: The extracted data is then preprocessed to correct common errors and formatted suitably for LLM analysis.
- LLM Application: The preprocessed data is analyzed using LLM to identify and extract personal and financial information accurately.
- Post Processing: This stage involves cross-referencing the LLM-extracted data with the initial OCR results to ensure consistency and accuracy.
- Result Delivery: Finally, EntrD receives the processed data, ready for anonymization and further use in their solutions.
Improvement from the LLM Solution
The improvements realized through this partnership and the integration of advanced LLM technology enable EntrD to enhance its anonymization and document masking processes significantly. This advancement fortifies EntrD’s position as a provider of advanced and reliable data security solutions within the tech industry.
EntrD will be participating in the fourteenth edition of CorporatiePlein 2024, on the 12th of September in Expo Houten, an event dedicated to the digital transformation of housing corporations. There, they will have the opportunity to showcase the results from the LLM solution’s implementation.
