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Data masking or data obfuscation is the process of modifying sensitive data in such a way that it is of no or little value to unauthorized intruders while still being usable by software or authorized personnel. Data masking can also be referred as anonymization, or tokenization, depending on different context.
When applied to metadata or general data about identification, the process is also known as data anonymization. Common strategies include deleting or masking personal identifiers , such as personal name , and suppressing or generalizing quasi-identifiers , such as date of birth.
Location data - series of geographical positions in time that describe a person's whereabouts and movements - is a class of personal data that is specifically hard to keep anonymous. Location shows recurring visits to frequently attended places of everyday life such as home, workplace, shopping, healthcare or specific spare-time patterns. [ 14 ]
De-anonymization is the reverse process in which anonymous data is cross-referenced with other data sources to re-identify the anonymous data source. [3] Generalization and perturbation are the two popular anonymization approaches for relational data. [4]
DataMask by AOL is a simple and secure software that disguises your personal data from cyber crooks and threatening websites by hiding your keystrokes (anti-keylogging) and diverting you away from sites designed to steal and use your personal information (anti-phishing). For more information, visit AOL DataMask webpage.
DataMask protects you by disguising your every keystroke. Ward off attackers with patented keystroke protection safeguarding your personal information.
To open DataMask, double-click the DataMask icon on your Windows system tray or click the Scrambler at the top of your web browser.
Pseudonymized data can be restored to its original state with the addition of information which allows individuals to be re-identified. In contrast, anonymization is intended to prevent re-identification of individuals within the dataset.