We often heard the news about hacking certain important sites, and stealing confidential data and transferring the money or purchasing something from credit/debit cards through card details, without interfering with the credit cardholder. All this happens by breaching the data masking.
This happens whenever the data is not secured or not masked. This has become a major issue in the present digital world. To overcome this type of issue data masking is necessary or essential. This data masking protects such activities from intruders.?
When intruders try to steal the data, this data masking helps in preventing the stealing of confidential data from servers.
Table of Contents
What is data masking?
Data masking refers to hiding sensitive content by changing certain values without disturbing the original data. The main aim of data masking is to provide some sort of security to the confidential data.?
The other names of data masking are Data scrambling, Data obfuscation, Data anonymization, and Data cleansing.
Data masking can be done through various procedures.?
Who uses data masking??
It is necessary for some enterprises to enhance better security strategies for incorporating best practices in data masking.??
There are different types of data which can be protected by various data masking types, and certain techniques help in securing the data. Below are the different types of data used in the business world.
- PII or Personally identifiable information
- PHI or Protected health information
- PCI-DSS or Payment card information
- ITAR or Intellectual property
What are the various types of data masking?
Various types of data masking they are.?
- Static Data Masking:
- Dynamic Data Masking:
- On-the-fly:?
1. Static Data Masking: It is the primary method of protecting data for specified elements. Sensitive data is masked in the original database, later the data duplicated in the test environment. Most of the specified elements will be columns and certain columns of the data fields.
These data fields contain information related to:
- Personally Identifiable Information (PII).
- Protected Health Information (PHI).?
- Primary Account Numbers (PAN).?
- Trade Secrets.
- Other Private Values.
2. Dynamic Data Masking: It is a type of masking which hides the data temporarily. Automation allows us to secure the data in real-time. When information masked with Dynamic masking, data never leaves even from the production database and less prone to threats.?
3. On-the-fly: This On-the-fly technique is similar to dynamic data masking technique. It occurs in the process of real-time. It utilizes a process called ETL which means Extract Transform Load, and masks the data inside the memory of the database application. This is mostly for agile companies which mainly target continuous delivery.?
Common Data Masking Techniques:
Following are the different types of common data masking techniques which are mostly used by the professionals.
- Encryption: Encryption which means hiding the data. Here the original data is encrypted with an algorithm which contains a key value. And this key value is sent to the particular end-user who is an authorised person. Original data is masked with an encryption algorithm. The end-user gets the original data by decrypting the key value. This is the very secured and complex type of data masking.
- Character Scrambling: Character scrambling is a very simple technique used to mask the data. In this technique, data is scrambled in such a way that it is unable to trace the original content.?
Here is a small example of how character scrambling is done.?
Ex: Original data is? Big data? which is scrambled as? Bad gati?.
- Nulling Out or Deletion: When an unauthorised person tries to access the data, the data gets deleted, or data becomes null.
- Number and Date Variance: Number and data variance is the technique mostly used to change or manipulate the data values of existing numbers and data. Values are changed to make the data obfuscate by certain random values specifying the range so that original data cannot be revealed. ?
- Substitution: Substitution is the technique which replaces the random values in original data, which looks like the original data but not related to the data. This technique doesn’t damage any feel and look of the data. This substitution technique protects the data from breaching.?
- Shuffling: Shuffle, which implies jumbling the data. This technique is similar to substitution, but in this shuffling, only particular field values are shuffled. This also doesn’t change the look and feel, but it cannot reveal the original data.?
What are the advantages of Data masking?
- It protects the data from breaching, data loss, service/ website/ account hacking, interfaces which are not secured, and malicious data by insiders.??
- Data masking doesn’t change the structural format and its integrity.?
- Without any fear, you can share the data to authorized people like developers and testers.
- Data masking reduces the data risks that are associated with cloud adoption.
- Data masking is cost-effective and less complicated than encryption, reducing the insider threat.
What are the Benefits of data masking?
- Your Data And Intellectual Property will be safe: You will need to be aware of security threats from hackers, viruses and malwares. All your information may expose all your details to open. Data masking helps in hiding all your personal details.?
- No need to Worry About your past Employee: When your employee leaves office, the employee may have all your company details, deals that had in the past. All these together lead to the misuse of your company prestige. Data is encrypted with levels of security, and data access is given to those people who have a certain level, which prevents stealing of such data and details.
- This Form Of Masking Is Highly Technical: Most of the people are using the same passwords for various accounts which makes the hackers crack your password so easily. But when you use data masking, Professionals come with new barriers and truncates the information which is not needed to be in a database.
Best practices of data masking :
Even Though we have many softwares, third party tools to control the breaching of data, but the hackers are still stealing the data with certain techniques in numerous ways. and such cases are getting increased as the intruders keep on inventing certain new ways to steal the data.?
Apart from implementing various data masking types, certain practises of data masking helps in protecting the data from intruders.??
- Use reversible methods: Use these irreversible methods to hide the data from intruders. By using a tool, transform the original confidential data to irreversible data, in such a way that the data cannot be retrieved back to original data in any form. The data should not be compromised even when the environment was changed. This method protects the data from intruders even when they try to manipulate data.
- Focus on the environment: Data undergoes certain environments like developing, testing, analytics and backup. During these environments, there are chances of data breaching. Data should be obfuscated during all these environments, and else data may get attacked by scammers and hammers. It’s very important to look and keep focused on all environments phases.
- Be quick to deliver the data: As the data keeps always changing on time. Companies should mask the data repeatedly and deliver the data through some secured channels. Whenever a company develops a data masking strategy, then companies should find ways to deliver the masked data safely and quickly.??
- Referential integrity should be maintained: Use certain tools to mask the data consistently. Data that took from various heterogeneous sources also should be masked constantly with the help of certain advanced tools. This ensures the values of data kept preserved even when the data transformation takes place.
- End to end approach: Organisation should not stop with just data masking; they have to identify the confidential data and implement certain standard obfuscation techniques. Finally, there should be certain audit resources claiming their protective strategies are working over this data.
- Find the data: This phase carries out identifying the data and categorizing the data as the data contain many data elements. This work is carried out by security analysts and business analysts mostly who combine the large data with a group of certain data elements.?
- Assess the situation: Security administrators will carry this situation. A security administrator is the only person who can determine the presence of sensitive information, ideal data masking technique and data location.
- Implement masking: For any giant organisation, a single data masking tool will not be feasible in masking the data for the entire enterprise.so masking should be implemented at various levels and look over future enterprise needs.?
- Test data masking results: This is the final phase where QA and testing is required to check whether masked data contains desired configurations or whether it is producing desired results. If they don’t find it, then the database administrator will revert data to pre-masked state and continue the masking process once again.?
Final thought:?
In this blog, we have discussed data masking importance, types and also certain techniques that help in protecting the data. Data masking provides a heightened sense of security to clients, employees and also many organisations.?
To protect crucial and confidential information, data should be masked with different techniques.?
Finally selecting the data masking technique and protection of data is based on the strategy, and the masking technology you want to use. Based on the complexity of data and storage (either cloud or database), the data should be masked.
In future we might evidence certain new data masking techniques with security-enhanced features may see. Further, certain industries may come with data masking techniques with certain analytical parameters may be seen.