Multi-dimensional data anonymization approaches (eg, Mondrian) ensure more fine-grained
data privacy by providing a different anonymization strategy applied for each attribute. Many …

In light of the escalating privacy risks in the big data era, this paper introduces an innovative
model for the anonymization of big data streams, leveraging in-memory processing within …

Background and Objectives: Nowadays, with the rapid growth of social networks extracting
valuable information from voluminous sources of social networks, alongside privacy …

Recent studies in data anonymization techniques have primarily focused on MapReduce.
However, these existing MapReduce based approaches often suffer from many performance …

Data privacy is a challenging trade-off problem between privacy preserving and data utility.
Anonymization is a fundamental approach for privacy preserving and also a hard trade-off …

The widespread proliferation of data collection has increased a serious privacy concern in
recent years. Data anonymization approaches have been proposed as a privacy-preserving …