A survey on privacy properties for data publishing of relational data
Recent advances in telecommunications and database systems have allowed the scientific
community to efficiently mine vast amounts of information worldwide and to extract new …
community to efficiently mine vast amounts of information worldwide and to extract new …
[Retracted] Privacy Protection of Healthcare Data over Social Networks Using Machine Learning Algorithms
S Khan, V Saravanan, GC N, TJ Lakshmi… - Computational …, 2022 - Wiley Online Library
With the rapid development of mobile medical care, medical institutions also have the
hidden danger of privacy leakage while sharing personal medical data. Based on the k …
hidden danger of privacy leakage while sharing personal medical data. Based on the k …
Toward trustworthy and privacy-preserving federated deep learning service framework for industrial internet of things
In this article, we propose a trustworthy privacy-preserving federated learning (FL)-based
deep learning (DL) service framework for Industrial Internet of Things-enabled systems. FL …
deep learning (DL) service framework for Industrial Internet of Things-enabled systems. FL …
DI-Mondrian: Distributed improved Mondrian for satisfaction of the L-diversity privacy model using Apache Spark
F Ashkouti, A Sheikhahmadi - Information Sciences, 2021 - Elsevier
For the extraction of useful patterns, the collected data should be distributed to and shared
with analyzers. This, however, creates problems and challenges for the individual with …
with analyzers. This, however, creates problems and challenges for the individual with …
Privacy preserving dynamic data release against synonymous linkage based on microaggregation
The rapid development of the mobile Internet coupled with the widespread use of intelligent
terminals have intensified the digitization of personal information and accelerated the …
terminals have intensified the digitization of personal information and accelerated the …
Privacy preservation in social network data using evolutionary model
S Srivatsan, N Maheswari - Materials Today: Proceedings, 2022 - Elsevier
Social Networks have seen an exponential increase in their user activity. The corresponding
user data can be extremely valuable, for improving user experience, identifying trends to …
user data can be extremely valuable, for improving user experience, identifying trends to …
[HTML][HTML] Cluster-based anonymity model and algorithm for 1: 1 dataset with a single sensitive attribute using machine learning technique
Privacy is a significant issue that requires consideration in all applications. Data collected
from various individuals and organizations must be disclosed to the public or private parties …
from various individuals and organizations must be disclosed to the public or private parties …
DHkmeans-ℓdiversity: distributed hierarchical K-means for satisfaction of the ℓ-diversity privacy model using Apache Spark
One of the main steps in the data lifecycle is to publish it for data analysts to discover hidden
patterns. But, data publishing may lead to unwanted disclosure of personal information and …
patterns. But, data publishing may lead to unwanted disclosure of personal information and …
Compressed sensing-based privacy preserving in labeled dynamic social networks
W Gao, J Zhou, Y Lin, J Wei - IEEE Systems Journal, 2022 - ieeexplore.ieee.org
With the rapid development of social networks, privacy-preserving is an important issue.
Nowadays, privacy-preserving mainly involves static social networks. In fact, social networks …
Nowadays, privacy-preserving mainly involves static social networks. In fact, social networks …
Generating Labeled Multiple Attribute Trajectory Data With Selective Partial Anonymization Based on Exceptional Conditional Generative Adversarial Network
Trajectory data generated in location-based service environments contain highly sensitive
personal information, making them a prime target for privacy attacks. At the same time …
personal information, making them a prime target for privacy attacks. At the same time …