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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.
However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index. Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a ...
Masking occurs when the same identifier is used for different entities in overlapping lexical scopes. At the level of variables (rather than names), this is known as variable shadowing . An identifier I' (for variable X') masks an identifier I (for variable X) when two conditions are met
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).
To open DataMask, double-click the DataMask icon on your Windows system tray or click the Scrambler at the top of your web browser.
To configure IP addresses on interfaces, masks start with 255 and have the large values on the left side: for example, IP address 203.0.113.129 with a 255.255.255.224 mask. Masks for IP ACLs are the reverse: for example, mask 0.0.0.255. This is sometimes called an inverse mask or a wildcard mask. When the value of the mask is broken down into ...
In Electronic Health Records (EHR's) data masking, or controlled access, [1] is the process of concealing patient health data from certain healthcare providers. Patients have the right to request the masking of their personal information, making it inaccessible to any physician , or a particular physician, unless a specific reason is provided ...
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...