Data anonymization helps to prevent which types of attacks in a big data environment?
Data anonymization helps to prevent which types of attacks in a big data environment?
Data anonymization helps to prevent correlation attacks in a big data environment. Correlation attacks involve combining various datasets to identify individuals or extract sensitive information that might not be directly identifiable in single datasets. By anonymizing data, such information is made less accessible, thereby reducing the risk of correlation attacks.
what s the problem, it s C. it s very obvious
The problem is that anonymization is the target for correlation attack, so it does not help avoiding it.
anonymization is the target for correlation attack, so it does not prevent it.
c is answer
C is the answer
involve analyzing multiple datasets or combining different sources of data to uncover sensitive or personally identifiable information. By anonymizing the data, the relationships between individuals, their attributes, and their activities are obfuscated, making it difficult for attackers to perform correlation attacks and gain insights into personal information.
Correlation attacks involve combining different datasets to identify individuals or sensitive information that may not be directly identifiable in individual datasets. By anonymizing data, such as removing personally identifiable information or aggregating data to obscure specific details, it becomes more challenging for attackers to correlate information across datasets and uncover sensitive or personal information.
c.correlation