Data Masking: Everything You Need to Know

Through the data masking process, critical data about school performance or student subject evaluations are encrypted or hidden. This is usually done in order to maintain the privacy of the owners of these datasets.

Data masking is also called data anonymization, data obfuscation, or pseudonymization. This process involves hiding confidential data by replacing them with fictitious functional data, which could be characters, words, or other data. Encryption, scrambling, variance, tokenization, redaction, deletion or nulling out, and character shuffling are other data masking techniques used often. The primary goal of data masking is to protect private, sensitive information by creating a version of data that can’t be reverse-engineered or deciphered.

Legislation like the FERPA (Family Educational Rights and Protection Act) has been created to safeguard students’ confidential data. It aims to ensure educators are held accountable for protecting their students’ data and are prohibited from revealing sensitive data to a third party without consent.

Data security isn’t something educational institutions can take lightly. Due to the emergence of online technology, several traditional educational institutions have shifted online to facilitate learning and even speed up specific administrative processes. From schools to higher educational institutes like colleges and universities, different facets of education have gone online, such as online courses, grading, communication, etc. Several administrative processes too are conducted online these days, such as admissions, CRM, finance, and human resources. As tens of thousands of students are served online, it has become a major challenge for schools, colleges, and universities to manage and secure sensitive data. Such data may be the students’ name, address, student number, social security number, medical history, grades, and religious beliefs. Data masking is used to protect such personal information and student records.

In the past, several major institutions have been adversely affected by high-profile data breaches. If sensitive student data falls into the wrong hands, it can be used, directly or indirectly, to identify the students and put them at the risk of being harmed. Some malicious elements could even sell them on the dark web or use them to commit identity theft, blackmail, or fraud. That’s why it has become extremely important to safeguard such data with data masking.

Data masking can help in situations where the institution shares confidential data with third parties. The process can also be used to hide student identities while maintaining reports and protecting educational institutions’ non-production environments when developing school applications.

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