Data Scrambling Vs Data Masking

Data Scrambling Vs Data Masking

As a cyber governance & risk management leader, I’ve had my fair share of dealing with sensitive data and staying ahead of the curve in the ever-evolving cyber landscape. In today’s fast-moving business arena, it’s more crucial than ever to ensure the confidentiality, integrity, and availability of sensitive data. Two key concepts that have garnered significant attention in recent years are data scrambling and data masking. But what exactly are they, and why do they matter?

What is Data Scrambling Vs Data Masking and why does it matter?

Data scrambling and data masking are two distinct techniques used to protect sensitive data in non-production environments. Data scrambling involves fragmenting and rearranging sensitive data to make it unreadable, while data masking involves replacing sensitive data with fictitious values that maintain the original structure and consistency. Both methods serve the same purpose: to safeguard sensitive data from unauthorized access and maintain compliance with regulatory requirements.

Imagine for a second your in a scenario where a developer is working on a new project and needs access to a company’s customer database. While it’s essential to provide the developer with a realistic dataset for testing, it’s equally crucial to protect the sensitive customer information from being exposed. This is where data scrambling or data masking comes into play. By using one of these methods, the developer can work with a simulated dataset that meets the project requirements while ensuring the confidentiality and integrity of the sensitive data.

A real-world scenario: transforming Data Scrambling Vs Data Masking for success

Recently, a leading global consumer goods company, Acme Corporation, faced a similar challenge. They needed to develop a new e-commerce platform while maintaining strict data privacy and compliance standards. The company’s IT team worked with Solix to implement a data masking solution that would allow developers to work with realistic datasets while safeguarding sensitive customer information.

• Automatically scan databases and applications to identify sensitive data
• Replace sensitive data with realistic but fictitious values
• Ensure that masked data retains its structure and consistency across applications and databases
• Comply with regulatory requirements such as GDPR and PCI DSS

By using Solix’s data masking solution, Acme Corporation significantly reduced the risk of data breaches, saved time and money, and ensured regulatory compliance.

How Solix saves money and time on Data Scrambling Vs Data Masking

Solix’s data masking solution is specifically designed to provide a cost-effective and efficient way to protect sensitive data. By automating the data identification and masking process, Solix saves organizations time and money by reducing the risk of data breaches and compliance issues.

• Cost savings: reduces the risk of data breaches and the associated financial and reputational costs
• Improved efficiency: allows developers and testers to work with realistic data without exposing sensitive information
• Simplified compliance: ensures regulatory compliance with strict data protection laws

Win $100!

Take the first step towards securing your sensitive data and improving your compliance posture. to be entered into a drawing to win $100.

Don’t miss out on this opportunity to learn more about Solix’s data masking solution and how it can help you transform your Data Scrambling Vs Data Masking approach.

About the author

As a cyber governance & risk management leader, I’ve had the privilege of working with companies like Unilever, AIG, Citi, GE, and Santander to help them achieve their cybersecurity goals. I’m passionate about writing about topics that can help businesses stay ahead of the curve in the ever-evolving cyber landscape, including Data Scrambling Vs Data Masking.