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Privacy preservation techniques in big data analytics: a survey
Incredible amounts of data is being generated by various organizations like hospitals,
banks, e-commerce, retail and supply chain, etc. by virtue of digital technology. Not only …
banks, e-commerce, retail and supply chain, etc. by virtue of digital technology. Not only …
[HTML][HTML] Differential privacy in edge computing-based smart city applications: Security issues, solutions and future directions
Fast-growing smart city applications, such as smart delivery, smart community, and smart
health, are generating big data that are widely distributed on the internet. IoT (Internet of …
health, are generating big data that are widely distributed on the internet. IoT (Internet of …
BIGSEA: A Big Data analytics platform for public transportation information
Abstract Analysis of public transportation data in large cities is a challenging problem.
Managing data ingestion, data storage, data quality enhancement, modelling and analysis …
Managing data ingestion, data storage, data quality enhancement, modelling and analysis …
Improving MapReduce privacy by implementing multi-dimensional sensitivity-based anonymization
Big data is predominantly associated with data retrieval, storage, and analytics. Data
analytics is prone to privacy violations and data disclosures, which can be partly attributed to …
analytics is prone to privacy violations and data disclosures, which can be partly attributed to …
Experimenting sensitivity-based anonymization framework in apache spark
One of the biggest concerns of big data and analytics is privacy. We believe the forthcoming
frameworks and theories will establish several solutions for the privacy protection. One of the …
frameworks and theories will establish several solutions for the privacy protection. One of the …
A re-identification risk-based anonymization framework for data analytics platforms
Preserving individual privacy is one of the major issues in the context of Big Data, since
handling huge volumes of data may contribute to the disclosure of sensitive or personally …
handling huge volumes of data may contribute to the disclosure of sensitive or personally …
An ensemble learning approach for privacy–quality–efficiency trade-off in data analytics
G Peethambaran, C Naikodi… - … Conference on Smart …, 2020 - ieeexplore.ieee.org
Privacy is an issue of concern in the electronic era where data has become a primary source
of investment for businesses and organizations. The value generated from data is put to use …
of investment for businesses and organizations. The value generated from data is put to use …
[PDF][PDF] Big data anonymization in cloud using k-anonymity algorithm using map reduce framework
Anonymization techniques are enforced to provide privacy protection for the data published
on cloud. These techniques include various algorithms to generalize or suppress the data …
on cloud. These techniques include various algorithms to generalize or suppress the data …
Progression study on privacy-preserving big data publishing techniques
V Chauhan, R Gupta - 2023 6th International Conference on …, 2023 - ieeexplore.ieee.org
In today's virtual world, it is vital to preserving privacy wherein the information is amassed
from different sources with sensitive information at an exceptional level had been the …
from different sources with sensitive information at an exceptional level had been the …
[PDF][PDF] Privacy preservation of data using efficient group cost optimization method with big data clustering
Huge amount of information is being produced by different associations like clinics, banks,
web based business, retail and production network, and so on by temperance of advanced …
web based business, retail and production network, and so on by temperance of advanced …