The publication of a patient's dataset is essential for various medical investigations and
decision-making. Currently, significant focus has been established to protect privacy during …

The topic of privacy-preserving big data analytics is gaining momentum now, thanks to the
plethora of modern application scenarios where it can be successfully applied. These range …

Most of the data publishing methods have not considered sensitivity protection, and hence
the adversary can disclose privacy by sensitivity attack. Faced with this problem, this paper …

Privacy preserving data publishing (PPDP) refers to the releasing of anonymized data for the
purpose of research and analysis. A considerable amount of research work exists for the …

The Internet of Things (IoT) is an exponentially growing emerging technology, which is
implemented in the digitization of Electronic Health Records (EHR). The application of IoT is …

Data publishing methods can provide available information for analysis while preserving
privacy. The multiple sensitive attributes data publishing, which preserves the relationship …

How can we orchestrate an one-off sharing of informative data about individuals, while
bounding the risk of disclosing sensitive information to an adversary who has access to the …

The overgeneralisation may happen because most studies on data publishing for multiple
sensitive attributes (SAs) have not considered the personalised privacy requirement …

Recent years have witnessed the wide availability of an array of transactional datasets for
mining and other research activities. A primary concern related to the public sharing of …

Because of the processing of continuous unstructured large streams of data, mining real-
time streaming data is a more challenging research issue than mining static data. The …