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As organizations aim to protect themselves from data breaches and comply with new privacy regulations, the need to protect sensitive data has never been more critical. In this article, we'll dive into the differences between encryption, data masking, and tokenization—essential tools in the arsenal of data security.
Think of encryption as a secure lockbox for your data. It involves converting plain text into an unreadable format using complex algorithms and a cryptographic key. It's like turning sensitive information into a secret code that only those with the right key can decipher. The result? A robust defense mechanism that ensures even if unauthorized eyes intercept the data, it remains a puzzle with no clear solution.
Example:
Plain text: Hello
Encrypted Text: jhoop
Consider a healthcare system employing encryption for secure transmission of patient records. When a doctor uploads medical information, it's encrypted on their device and transmitted securely. Even if intercepted, the data remains unintelligible without the decryption key. At the central database, it's decrypted, ensuring patient data confidentiality and integrity throughout the process.
Masking is like putting on a disguise for specific portions of your data. It involves concealing certain elements, making them unreadable to unauthorized users. Unlike encryption, masking is a one-way street – it allows for the protection of selected data elements while keeping the overall structure intact. This technique is handy when you want to show only part of the information, like hiding digits in a credit card number.
Example:
Plain text: Hello
Masked Text: H####
For organizations that leverage call centres in foreign countries, data masking may be used to hide a customer's sensitive information from unauthorized employees. While authorized users within the organization's country may have access to the customer's SIN, displayed as 123456789, call centre employees are restricted to viewing only a masked version, displayed as ######789.
Tokenization takes a unique approach by substituting sensitive information with a non-sensitive equivalent, known as a token. This token holds no intrinsic value and reveals nothing about the original data. Even if intercepted, the token is meaningless without the corresponding mapping to the original data, which is securely stored elsewhere. This method is highly effective when the actual data isn't needed for processing, reducing the risk of exposing sensitive information.
Example:
Original value: Hello
Token: Orange
Imagine an e-commerce platform that stores customer credit card information. To enhance security and comply with PCI DSS (Payment Card Industry Data Security Standard), the platform employs tokenization.
When a customer initially provides their credit card details, the platform doesn't store the actual card data. Instead, it generates a unique token—a meaningless, non-sensitive placeholder. This token is securely stored in the platform's database, while the actual credit card details are sent to a tokenization provider.
For subsequent transactions, the platform uses the token to reference the stored credit card information without actually possessing or exposing the sensitive data. Even if a security breach occurs and the token is intercepted, it holds no value without the corresponding mapping to the original credit card details.
Understanding these three techniques is crucial for building a robust data security strategy tailored to your needs.
In a world where data is a valuable asset and a potential liability, understanding the straightforward distinctions between encryption, masking, and tokenization is imperative. Implementing these techniques strategically is key to maintaining the integrity and confidentiality of sensitive information in an ever-evolving digital landscape.
To create a robust security strategy for your organization, talk to a DataStealth expert today.