Sensitive data must be managed with stringent controls in place to keep it secure from a breach or malicious use of data. Data masking is essential to reduce the risk of critical threats: data loss, exfiltration, insider threats, or account compromise.
Protect sensitive data with ease
Through Quantum’s data masking services, we enable businesses to use crucial business data for training and testing without having to worry about the actual data leaking. We provide secure, flexible, and efficient data masking solutions for businesses in all sectors.
Safeguard business and client data while utilising the benefits of data assets across all document types.
Our data masking methodology & techniques
Our technologies comprise solutions made to desensitise data in order to protect it from privacy or confidentiality violations. With the help of these technologies, businesses may strategically reduce the footprint and spread of critical data, whether it is contained within invoices, medical records or many other use cases.
Depending on the data type, a number of data management approaches can be used to mask or anonymise PII and other private and sensitive data. The following are some of the masking techniques we employ depending on the use case:
ScramblingAlphanumeric characters are scrambled randomly. For instance, after being scrambled, a ticket number from a production environment would show up differently in a test environment. Scrambling is a simple method but it only works with specific kinds of data and can be less secure than other methods.
SubstitutionThis method substitutes another value from a pool of credible values. Lookup tables frequently offer other values in place of the actual, sensitive data.
With this technique, a date field is increased or decreased by a certain date range. The range value should be kept secure.
Information about financial and transaction value and date is frequently concealed by applying a variance. Each date or number in a column is altered by a random percentage of its true value via the variance algorithm.
Masking out is typically used on credit card numbers and scrambles a portion of a value.
When a data column is nullified, the actual values are swapped out with a null value, entirely hiding the data.
Why companies choose Quantum for data masking
When it comes to data masking, we are proud to be fast and reliable – with no room for error.
We will ensure your organisation meets compliance requirements so that sensitive data cannot slip through the net.