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What is an Element Mask?
In application modeller, element mask−which enables you to replicate the attribute selection of one element and apply it to others−is the way of the future.
You may determine which characteristics should be used by various application model components (eg. Class Name, Window Text, W and Z). This may be done by creating an element with the required characteristics, copying and pasting the element's "Element Mask," and then creating the extra elements.
This will allow the same attributes in the target element that are enabled in the source element and set the match types (Equals, Greater Than, etc.) to the same. Be mindful that just the "In Use" and "Match Type" settings−not the values−will be altered by this.
An attribute mask may be copied by selecting Copy Element Mask from the context menu of the source element.
Apply an element mask by choosing Paste Element Mask from the context menu of the right−clicked element.
Advantage of element masking
The advantages of element masking are as follows −
It provides workable protection against the following five threats− data breaches, data loss, account or service takeover, insecure interfaces, and insiders abusing data.
The masked piece retains the format and integrity of its structural design.
Without worrying that production data would be compromised,Element may be shared with authorized persons like developers and testers.
Significantly reduces the data dangers posed by rising cloud adoption.
Mitigates the risk of insider threats, is less expensive, and is easier to use than encryption.
Masking techniques
Several data masking techniques are used to protect the data. Notable among them are −
Substitution − Substitute values with ones that are equal. Consider substituting names of the same gender for others.
Shuffling − Randomly and vertically shuffle the values in the column. Linkages to sensitive data should be separated from this.
Blurring − Modifying an existing value within a certain range.
Tokenization − The replacement of data components with arbitrary placeholder values.
Dynamic Element masking
The process for hiding production data at the time the data request is actually made is known as dynamic element masking. View−based and proxy−based dynamic masking are the two types available.
The production version of the data and the masked version are stored in the same database when using view−based masking. Users who are denied access to production data or who otherwise transgress the security filter see masked data displayed on their screens.
Proxy−based masking adds another layer of proxy security between the user and the database. When a user query passes through a proxy, the proxy replaces the query result with masked data. This provides data protection without requiring a change to the database.
Queries can be redirected to get data from hidden columns using a contemporary technique called query substitution. In addition to other possibilities, these searches can choose masked data from a view or file or link to another database.
Enterprises cannot afford to forgo the cloud because of security concerns given the benefits it provides, despite the fact that cloud infrastructure has lately been exposed to security threats. Data masking is one technique for boosting cloud security. The market for data masking is expected to grow by 30–40% yearly as companies become more concerned about internal and external security breaches, according to analysts. You may benefit from the benefits of the cloud without compromising security if you employ masking correctly.
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