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In data sanitization, HTML sanitization is the process of examining an HTML document and producing a new HTML document that preserves only whatever tags and attributes are designated "safe" and desired.
In addition, DOMPurify parses the id and name attributes of injected elements to identify if they can collide with existing global functions. [21] However, recent vulnerabilities related to DOM clobbering have been found in DOMPurify and similar libraries such as HTML Janitor, which indicate that these libraries only protect against specific ...
One type of data sanitization is rule based PPDM, which uses defined computer algorithms to clean datasets. Association rule hiding is the process of data sanitization as applied to transactional databases. [32] Transactional databases are the general term for data storage used to record transactions as organizations conduct their business.
Redaction or sanitization is the process of removing sensitive information from a document so that it may be distributed to a broader audience. It is intended to allow the selective disclosure of information.
Censorship, editing that prevents sending or publishing sensitive information or unapproved opinions; Data sanitization, actions taken to prevent unscrupulous recovery of information that has been deleted from storage media
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]
A code sanitizer is a programming tool that detects bugs in the form of undefined or suspicious behavior by a compiler inserting instrumentation code at runtime. The class of tools was first introduced by Google's AddressSanitizer (or ASan) of 2012, which uses directly mapped shadow memory to detect memory corruption such as buffer overflows or accesses to a dangling pointer (use-after-free).
Data anonymization has been defined as a "process by which personal data is altered in such a way that a data subject can no longer be identified directly or indirectly, either by the data controller alone or in collaboration with any other party."