Distributed computing in multi-agent systems: a survey of decentralized machine learning approaches
At present, there is a pressing need for data scientists and academic researchers to devise
advanced machine learning and artificial intelligence-driven systems that can effectively …
advanced machine learning and artificial intelligence-driven systems that can effectively …
[PDF][PDF] Hybrid Approach for Privacy Enhancement in Data Mining Using Arbitrariness and Perturbation.
B Murugeshwari, S Rajalakshmi… - … Systems Science & …, 2023 - cdn.techscience.cn
Imagine numerous clients, each with personal data; individual inputs are severely corrupt,
and a server only concerns the collective, statistically essential facets of this data. In several …
and a server only concerns the collective, statistically essential facets of this data. In several …
Differential privacy may have a potential optimization effect on some swarm intelligence algorithms besides privacy-preserving
Z Zhang, H Zhu, M **e - Information Sciences, 2024 - Elsevier
Differential privacy (DP), as a promising privacy-preserving model, has attracted great
interest from researchers in recent years. At present, research on the combination of deep …
interest from researchers in recent years. At present, research on the combination of deep …
Multi-label clinical time-series generation via conditional GAN
In recent years, deep learning has been successfully adopted in a wide range of
applications related to electronic health records (EHRs) such as representation learning and …
applications related to electronic health records (EHRs) such as representation learning and …
Private true data mining: Differential privacy featuring errors to manage Internet-of-Things data
Available data may differ from true data in many cases due to sensing errors, especially for
the Internet of Things (IoT). Although privacy-preserving data mining has been widely …
the Internet of Things (IoT). Although privacy-preserving data mining has been widely …
Re-identification in differentially private incomplete datasets
Efforts to counter COVID-19 reaffirmed the importance of rich medical, behavioral, and
sociological data. To make data available to many researchers who can conduct statistical …
sociological data. To make data available to many researchers who can conduct statistical …
Blockchain application analysis based on IoT data flow
J Li, X Zhang, W Shi - Electronics, 2022 - mdpi.com
In the Internet of Things (IoT) system, data leakage can easily occur due to the differing
security of edge devices and the different processing methods of data in the transmission …
security of edge devices and the different processing methods of data in the transmission …
PRIMϵ: Novel Privacy-Preservation Model With Pattern Mining and Genetic Algorithm
This paper proposes a novel agglomerated privacy-preservation model integrated with data
mining and evolutionary Genetic Algorithm (GA). Privacy-pReservIng with Minimum Epsilon …
mining and evolutionary Genetic Algorithm (GA). Privacy-pReservIng with Minimum Epsilon …
Multi-sensor Data Privacy Protection with Adaptive Privacy Budget for IoT Systems
In the era of pervasive sensing and data-driven decision-making, the Internet of Things (IoT)
has become ubiquitous, with sensors serving as the fundamental building blocks of IoT …
has become ubiquitous, with sensors serving as the fundamental building blocks of IoT …
Towards practical and privacy-preserving CNN inference service for cloud-based medical imaging analysis: A homomorphic encryption-based approach
Y Bai, H Zhao, X Shi, L Chen - Computer Methods and Programs in …, 2025 - Elsevier
Abstract Background and Objective: Cloud-based Deep Learning as a Service (DLaaS) has
transformed biomedicine by enabling healthcare systems to harness the power of deep …
transformed biomedicine by enabling healthcare systems to harness the power of deep …