Managing and safeguarding sensitive data has gained significant priority for businesses across the spectrum. From enterprises collecting customers’ personal information to health organizations handling confidential patient data, all are faced with the challenge of protecting this vital data. Data breaches can undermine an organization’s credibility, breach laws, and result in significant financial losses for both the responsible organization and the individuals themselves. Therefore, companies are resorting to different strategies and methods like data masking and encryption to safeguard their sensitive information. This blog post seeks to expound on these two popular methods, elucidating their working mechanisms, advantages, and the scenarios in which they’re most efficient.
Often you might have heard the term data masking, but what does it mean? Simply put, data masking refers to a method where sensitive, specific details are replaced or concealed with other data so that the original content stays safe from unauthorized users. There are largely two types of data masking that are commonly applied, known as static data masking and dynamic data masking.
Static data masking deals with protecting sensitive data in non-production environments. It involves creating a sanitized copy of the production data and replacing the sensitive values with fictitious but realistic values. On the other hand, dynamic data masking doesn’t alter the actual data. Instead, it hides the real data that is at rest from the users who are not supposed to see it, providing them with a masked view of the data. This method is particularly popular for real-time testing purposes, preserving referential integrity without uncovering the original data.
Now, why would an organization want to use data masking? There are quite a few reasons. Data masking helps protect sensitive information like social security numbers, credit card numbers, and other personally identifiable information (PII) from unauthorized access. It plays a pivotal role in maintaining data privacy in software testing and regulatory compliance. Moreover, data masking techniques utilizing data obfuscation and SQL servers help maintain data security, ensuring that your masked data remains safe.
For instance, let’s say a company is developing a new application that processes credit card transactions. For testing purposes, they must use data that mirrors what real customers would provide. Instead of risking real credit card numbers, the company could apply data masking to generate representative data that would serve for testing purposes. This allows the company to safeguard the original data, reduce the likelihood of a data breach, and stay compliant with relevant privacy regulations like the Payment Card Industry Data Security Standard (PCI DSS).
In essence, data masking proves to be a valuable tool in any database administrator’s toolkit, allowing the secure use of sensitive information across different spheres of an organization’s operation.
As we continue our exploration of data security methodologies, let’s delve into the realm of data encryption. Encryption is a powerful method employed to convert readable data, or plain text, into unreadable characters known as ciphertext, using an encryption algorithm and an encryption key. The concept behind it is to make your data unreadable to any unauthorized users, thereby preventing data breaches and unauthorized access.
It relies heavily on two key components – the encryption key and the decryption key. The encryption key transforms the original data into an unreadable format using an encryption algorithm, while the decryption key serves to convert the encrypted data back to its initial form. This process can happen through various techniques, one of which is format-preserving encryption (FPE). FPE guarantees that encrypted data remains the same length as the original content, ensuring that systems designed to process specific formats are not disrupted.
However, just as with any other method, data encryption has both its merits and challenges. On the positive side, it offers a high level of security for data in transit or at rest, making it an excellent choice for securing sensitive information stored in databases or transmitted via insecure networks. Its multi-key system assures that even if an unauthorized person obtains the encrypted data, they would not decipher it without the correct decryption key.
On the downside, encryption has a few drawbacks such as the risk of losing the decryption key, which could result in permanent data loss. Encryption also introduces certain complexities in the data access and retrieval process, potentially slowing down data operations.
Despite these challenges, data encryption remains a fundamental approach to securing sensitive and unstructured data. For instance, a health organization storing digital health records would need to ensure this information remains confidential. Encryption would shield this sensitive data, maintaining its privacy and integrity. At its core, data encryption serves as an exemplary methodology, providing robust security layers to original content or data, making it an integral part of today’s enterprise-level data security strategies.
Now that we have explored data masking and data encryption separately, it’s time for a comparative analysis of the two. Each one has its unique strengths and particular contexts in which it offers superior advantages.
Data masking excels when it comes to preserving the format and integrity of the original data while hiding sensitive details. This makes it an excellent choice for software testing and use in non-production environments where realistic data is needed but revealing sensitive information is undesirable. Data masking ensures referential integrity while reducing the potential for unauthorized access or data breaches, making data management an easier task for database administrators.
On the other hand, encryption is recognized for its strength in protecting data at rest or in transit – be it on physical storage mediums or across digital networks. The biggest advantage of encryption lies in its ability to make unauthorized access impossible without the correct decryption key.
However, selecting between data masking and encryption isn’t about choosing which one is universally better—it’s about aligning the strengths of each technique with your precise needs. If your primary need is to protect actual content at rest or during transmission, encryption might be your best option. Alternatively, if you need to use real data in a readable format without revealing sensitive details—for example, during software testing or database engine development—then data masking could be the most suitable.
Naturally, the decision-making process entails a thorough understanding of your specific context, the regulatory requirements you need to abide by, the type of data you’re handling, and the cost and infrastructure implications. Data masking or encryption – the choice ultimately hangs on these factors. So as you deliberate, remember to focus on the method that best serves your organization’s unique needs. In the end, these two views on securing sensitive data need not be mutually exclusive; many businesses utilize a combination of data masking and encryption on different tiers of their operation.
For many organizations, deciphering the complexities of data masking and encryption, and determining which strategy is most suitable can be an overwhelming task. That’s where Duality Tech steps in. At Duality, world-class cryptographers and expert data scientists are revolutionizing how businesses handle sensitive and identifiable information. Duality Tech’s advanced technology deploys secure analysis on encrypted data, all while complying with rigid data privacy regulations. By spearheading the innovative use of Privacy Enhancing Technologies (PETs), Duality is empowering organizations with the ability to collaborate securely on sensitive data, from financial information to clients’ details and more.
In the context of the topics we’ve explored thus far – data masking and encryption – Duality provides groundbreaking technology that leverages the best of both worlds. Our robust solutions bring together the format-preserving capabilities of data masking with the stringent security systems of encryption, attaining both referential integrity and robust protection against unauthorized access. This innovative approach allows businesses to not only secure their data but also maximize the value they derive from it. Customers, suppliers, partners – an entire business ecosystem can interact confidently, knowing that sensitive data is being handled with the utmost level of security.
Duality’s Technologies has proven itself across many industries and government organizations, featuring partnerships with DARPA and the World Economic Forum (WEF), due to our contribution to safe collaborative data analysis. Our commitment to ensuring secure collaborative data analysis has made us a trusted choice, bolstered by our 314b standing in the US Financial sector and validation from the UK ICO regarding our encryption methods. Our technology meets the latest privacy requirements by ensuring that it is impossible to identify the data subject, a level of security that methods like tokenization and deidentification can’t match. Unlike data masking, which compromises data quality for privacy, our use of Fully Homomorphic Encryption (FHE) allows the entire dataset to remain intact for high-quality analysis without exposing sensitive information. Whether you’re a business owner grappling with complex data privacy issues or a database administrator safeguarding your organization’s data, Duality has the solution for you.
