In recent years, protecting the organization’s crucial data in the non-production environment has turned out to be one of the critical functions. The sensitive and relevant information should be substituted with reasonable values. This permits production data to be securely used for testing, development, and outsource partners or other non-production uses.
Organizations have taken the data security threats seriously and have expanded to deal with these problems as fast as possible knowing the effects. Though the concept of merely eliminating sensitive data from non-production environment appears to be easy, it can cause severe challenges in a range of facets.
Some challenges that need immediate attention are:
- Classifying sensitive information.
- What identifies sensitive information?
- Where is it located?
- How is it set down?
Applications have grown to be extremely complicated and integrated. Having knowledge of where the sensitive information is located and what applications are referencing this data has become an intimidating task. Leading with the increasingly developing application, sustaining meta-data information of the application’s structural design during its life-cycle also becomes a challenge.
After identifying the sensitive information, the procedure of masking at the same time as maintaining integrity of application becomes vital. The application that is employed for testing, developing or upgrading will inadvertently break down if the value is changed simply. For instance- masking an element of a client’s address, such as zip code exclusive of reflecting on city and state, may leave the application inoperative.
Another challenge that is seriously considered is auditing. An important business control requirement to establish observance with regulations and laws is having knowledge of who changed what and when. To execute these kinds of control measures, the challenge happens to be a division of responsibilities, role based authorizations and the skill to give a report on these actions.
Over the years, the rate of requests for a protected non-production environment to be accessible has hugely increased as the size of databases is also increasing. The data masking techniques should offer satisfactory performance and consistency. In conclusion, having a solution that is flexible and can develop with the application and continue to other applications inside an organization becomes a significant challenge to deal with.