Thus it may be easy to think of data masking and data encryption as the same things, since they are both data-centric means of protecting sensitive data. However, it is their inherent procedures and purposes that differentiate them.
Data masking software from IRI protects PII in with a wide array of protection functions, including encryption , redaction with masking characters, hashing , pseudonymization , randomization, toenization, random noise, etc. This section of the IRI web site, and this section of the IRI blog site contain more information on data masking and encryption. Both these terms are indeed different.
Data encryption is used to encrypt data so that only people having secret key can access it, whereas data masking creates structurally similar but inauthentic versions of data. Thank you for this briefing on methods. Thanks for sharing the information, you cleared my confusion regarding data masking and data encryption. Your information was vital. Can the tool provide encryption to certain fields while obfuscate other fields? Check here to Subscribe to notifications for new posts.
Skip to content. When would you choose to use data masking vs data encryption? CoSort 9. What is Data Pseudonymization? Yes, it is not a deterministic algorithm. We agreed with the other party to use a symmetric key same key for encryption and decryption — just decrement 1 from each digit of the SSN and get the original SSN data from the encoded one. Bob encodes the sensitive data, such as an SSN, by incrementing each digit by 1and sends it to Joye.
Joye knows the decryption key, so she decodes the SSN and can access the original data. Note: In principle, it is possible to break the encryption algorithm. By a brute force approach, we can try all possible key combinations and break the encryption algorithm. However, the quantum of time to search all possible keys is a huge order of 10 to the power 27 years if, for example, we are using a bit encryption key.
It is the size of the key that makes breaking the encryption algorithm harder and harder. In , a bit RC4 key was cracked in only 3. So, the strength of the encryption algorithm. The process of providing a safeguard to original data through obfuscating field-level data attributes is termed data masking and the data set is called masked data.
For example, using an SSN, we could mask the first five digits, while still leaving the last four available for user validation—what you often encounter when calling a customer support center. Another way to think of it, in data masking methodology, we may not have to reconstruct original data to still achieve some usability while desensitizing the data. It helps to point out the most fundamental difference between encryption original data is transformed into encoded data and original data is restored from it and data masking no transformation, just original data is protected to achieve data anonymization.
The most significant property of data masking is: Data masking methodology does not require data to be reversible. The strength of data masking methodology is data masking can be done in such a way that there is no way to retrieve original data from masked data when not required. It is typically a one-way transformation, much like hashing.
The real data was replaced and is gone forever. The data shared between you, your bank, and the electric company must be unreadable by anybody who intercepts it. The actual information is still there. But only you, your bank, and the electric company have the encryption key. Your bank wants to bring you innovative product improvements. These developers must validate their code using data they know has actually been used to make successful transactions.
So the bank masks this data. Real names, addresses, bank balances, and all other sensitive personal information is replaced with fictional data. It will simulate bank customers, but they could never be identified by it. The developers can use it to validate real-world scenarios. It also determines which data protection method should be used.
No matter how many times it travels or where it goes, it ultimately must be restored to the original state. Information with this requirement is often called production data. The masking process of converting sensitive personal data is also called anonymization or de-identification.
0コメント