How to mask an email address
Email masking is more critical than ever before. Hide the data behind your address for privacy.
Table of contents
- What is email masking?
- Use cases of email-masking
- Masking your users' email
- Forms of data masking
- Masking emails in a database
- How to update each record with a random address
- Hashing records
- Email Masking Services
- Microsoft SQL Server data masking
- IRI field shield
- Oracle data masking and submitting
- Is Masking Emails For Testing a Good Idea?
Email masking has become more critical than ever before. Whether you wish to secure your email address or those of thousands of your clients, we may have something useful for you.
What is email masking?
Email masking is altering email addresses to hide the actual data. Usually, a masked email address keeps its original format and can't be easily traced back to the exact address. It's often part of a data masking process where sensitive data, such as Social Security or credit card numbers, are transformed.
Use cases of email-masking
The difference between masking your email address and a database of user emails is largely down to the individual's privacy settings.
Masking your users' email
Many data protection laws give strict guidelines on how user data must be handled. There are plenty of legitimate reasons for creating new copies of your users' data. Masking each piece of data is just an intelligent thing to do, and IBM has the numbers to support it.
Forms of data masking
Data masking is the process of turning copies of a database into a new set of data. There are several approaches to data masking, including Dynamic Data Masking (DDM) and Static Data Mapping (SDM). The main goal of DDM is to enforce role-based security for databases.
Masking emails in a database
Email is often masked to be used later for software testing. 61% of respondents of Red Gate's Data Governance Survey admitted to using production data for non-production purposes. There are several simple techniques for email masking with the respective SQL queries. These queries to assist you in getting the email masking best practices and questions are ;
How to update each record with a random address
You could generate thousands of fake email addresses on your @emailtestingis.cool domain. This method solves this problem without adding much complexity. If you realize something is wrong during the QA process, you'll be able to trace back to the origin of the problem quickly.
Another approach for securing data involves turning emails into a useless set of hashes. This makes for a pretty solid security layer for any other purposes. HASHBYTES is a built-in function that does all the work for you. It supports the most common algorithms from MD and SHA families.
Email Masking Services
Microsoft SQL Server data masking
Microsoft's Dynamic Data Masking tool protects sensitive data from being exposed to non-authorized users. Since the masking is dynamic, the data is not cloned and amended. It is a feature of Microsoft's latest version of its database management software (2016 and newer).
Dataprof is dedicated to turning production data into realistic, synthetic data. It bypasses triggers, indexes, and constraints to get the data you need for proper software testing. The company also ensures users' basic information is preserved while protecting their privacy and data integrity.
IRI field shield
It can mask data using various methods and rules, including encryption, pseudonymization, and redaction. It's known for its high performance and affordable pricing - starting at just $9.99 per GB.
Oracle data masking and submitting
The Oracle Tool is great for securing existing data and creating high-quality test data. It features automatic detection and masking of sensitive data, removing duplicates, and cleaning databases. It supports Oracle databases and MySQL, SQL Server, Sybase, and others like masking your email addresses.
Is Masking Emails For Testing a Good Idea?
Even the most sophisticated tools for your mask email address might eventually go wrong. You may accidentally skip some records in your DB. The masking algorithm may not correctly handle some of the emails. Errors may prove to be hard to catch for an extensive data set.
By sending test emails to dummy accounts, you also hurt your deliverability. This will look like a mailing to an inferior quality list to email servers.