The phrase "a sensitive attribute of" is correct and usable in written English.
It can be used when discussing characteristics or features that are delicate or require careful handling, often in contexts like data privacy or personal information.
Example: "In our analysis, we must consider a sensitive attribute of the user's profile to ensure their privacy is protected."
Alternatives: "a delicate characteristic of" or "a confidential feature of".
The method is tailored for the joint estimation of the proportion of individuals in the population bearing a sensitive attribute and the proportion of individuals in the sensitive group declaring truthfully their status.
An equivalence class is said to have t-closeness if the distance between the conveyance of a sensitive attribute in this class and the distribution of the attribute in the whole table is less than a threshold t.
The second type of disclosure is when an adversary learns a sensitive attribute about a patient in the database with a sufficiently high probability without knowing which specific record belongs to that patient [ 32, 34].
It analyzes the data partitioning technique and algorithmically develops this technique to build privacy-preserving indices on sensitive attributes of a relational table.
MDSBA presumes a table model with a set of Q-IDs and one sensitive attribute (S), known by a Class.
The problem with this method is that it depends upon the range of sensitive attribute.
For instance, Table 3 contains four values of sensitive attribute (Cancer); these are {no positive histology, Positive histology, Positive microscopic confirm, and Positive laboratory test}.
In k-anonymization, if the quasi-identifiers containing data are used to link with other publicly available data to identify individuals, then the sensitive attribute (like disease) as one of the identifier will be revealed.
Despite the fact that k-anonymity can prevent identity attacks, it fails to protect from attribute disclosure attacks because of the lack of diversity in the sensitive attribute within the equivalence class.
Eight Place – Baiduri Bank, a QAB to be from Brunei Darussalam and it's ethnic sensitive attribute was ranked least by this set of respondents with 1.39%.
