Data Masking vs Encryption: Are you using the right data security tool?
- Data Masking removes sensitive information and replaces it with similar data to create a masked version of the original sensitive data
- Data Masking is useful for securing structured data that needs to maintain its utility, like credit card numbers, social security numbers, and other personally identifiable information
- Data Encryption uses complex algorithms to change data until it is unreadable. It can be decrypted with the corresponding encryption key
- Data Encryption is useful for securing unstructured data that is being sent over different networks or stored for an extended period of time
If you’re looking for a data security solution, you’ve probably heard of both data masking and data encryption tools. But what is the difference between these two tools? Is one better than the other? Understanding how data masking and data encryption work, and how they differ, will help you choose the best tool for the data you are looking to protect.
What is Data Masking?
Data masking, also known as data de-identification, replaces sensitive values with algorithmically determined values to mask the sensitive data. By replacing key parts of the sensitive data, masked data can be separated from identifiable persons or rendered useless for malicious purposes. This creates a functional version of the data that cannot be compromised by hackers and stays out of scope for compliance.
Data Masking vs Tokenization
If you’re reading this definition and it sounds familiar, you may wonder what the difference is between data masking and tokenization. The reality is that these two terms are connected, and tokenization is simply a tool used for data masking.
Types of Data Masking
Data masking uses multiple tactics to change data and obfuscate sensitive information:
- Static Data Masking – Static data masking creates a desensitized version of the data for functionality purposes in the original database and sends the backup copy to a different location.
- Dynamic Data Masking – Dynamic data masking stores the data within other systems in a development environment. This means the data can be secured on-demand without leaving the development environment.
- On-the-Fly Data Masking – On-the-fly data masking uses an Extract-Transform-Load (ETL) process to mask data within the development environment itself instead of using another system or staging environment.
Data Masking for Compliance
Data masking is particularly helpful for compliance efforts, whether thatâ€™s PCI DSS compliance, CCPA compliance, GDPR compliance, or HIPAA compliance. For GDPR, data masking can act as a pseudonymization tool if it separates the data from its data subject. For HIPAA, data masking practices can also help meet de-identification requirements. Some companies even have SaS data masking offerings, which makes this solution easier for companies to implement.
What is Data Encryption?
Encryption converts original sensitive data into an unreadable version of the data using complex algorithms. In order to decrypt the data, an encryption key is needed to effectively revert the data back to its original form. However, decryption can be brute-forced by malicious actors, so encrypted data is often still considered sensitive data.
Additionally, in order to use encrypted data, the data needs to be decrypted so it can serve its purpose. This can put the data at risk when it’s in use. Because of this, encryption works well for data that needs to be secure, but not functional. Encryption is a particularly helpful tool for data at rest, or data in storage.
Data Masking vs Data Encryption
Data masking secures data by removing either a part of the sensitive data, replacing it with a “mask” with a similar structure but a different value. Encryption on the other hand uses complex algorithms to change the sensitive data until it is unreadable without a key.
Both of these tools have the same goal: data protection. Since they achieve the same goal in slightly different ways, they are both helpful for different data protection goals. Comprehensive data security strategies will often employ both tools to secure data across an organization. Let’s look at their fundamental differences, and what problems they best solve.
Data Masking Uses
Data Masking is a persistent data security solution, it secures data at every part of the process, whether it’s at rest, in motion, or in use. It works especially well for data that has consistent formatting, like social security numbers or credit card numbers. By masking part of the data, other key parts of the data (like the last four digits of a credit card number) can be safely seen, and the data utilized.
Data masking leaves no identifiable links to the original sensitive data, which makes it useless to hackers. Additionally, it works to ease the burden of many compliance regulations by desensitizing the data completely.
Data masking is particularly helpful for securing structured data that needs to be functional.
Consider data masking for:
- Credit Card Numbers and Other Payment Information
- Social Security Numbers
- Patient Information
- Personally Identifiable Information (PII)
Data Encryption Uses
Data encryption is a remarkably secure method that protects data from unauthorized access. While it technically is reversible without an encryption key, advanced encryption methods are close to impossible to break. This makes well-encrypted data only vulnerable to advanced hackers with a lot of brute force.
Encryption secures data by making it unreadable without decrypting it with an encryption key. While this effectively secures the data, it also sacrifices the data’s functionality for its security. It also means the data is more vulnerable when it is in use, which brings the data into much more strict compliance requirements.
Encryption is particularly helpful for securing unstructured data that is being transferred between networks or stored for longer periods of time.
Consider encryption for:
Data masking and data encryption are both remarkably helpful data security tools. Understanding how they differ will help you choose the data security solution that best fits your needs.