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A comprehensive survey on secure outsourced computation and its applications
With the ever-increasing requirement of storage and computation resources, it is unrealistic
for local devices (with limited sources) to implement large-scale data processing. Therefore …
for local devices (with limited sources) to implement large-scale data processing. Therefore …
K-means clustering and kNN classification based on negative databases
Nowadays, privacy protection has become an important issue in data mining. k-means
clustering and kNN classification are two popular data mining algorithms, which have been …
clustering and kNN classification are two popular data mining algorithms, which have been …
{SANNS}: Scaling up secure approximate {k-Nearest} neighbors search
The k-Nearest Neighbor Search (k-NNS) is the backbone of several cloud-based services
such as recommender systems, face recognition, and database search on text and images …
such as recommender systems, face recognition, and database search on text and images …
Motor imagery based brain-computer interface: improving the EEG classification using Delta rhythm and LightGBM algorithm
This article contains a new method to improving the EEG motor imagery classification
system quality with an application on BCI competition IV 2a, 2b, and PhysioNet EEG-MI …
system quality with an application on BCI competition IV 2a, 2b, and PhysioNet EEG-MI …
Toward highly secure yet efficient KNN classification scheme on outsourced cloud data
Nowadays, outsourcing data and machine learning tasks, eg,-nearest neighbor (KNN)
classification, to clouds has become a scalable and cost-effective way for large scale data …
classification, to clouds has become a scalable and cost-effective way for large scale data …
Privacy-preserving K-nearest neighbors training over blockchain-based encrypted health data
RU Haque, ASMT Hasan, Q Jiang, Q Qu - Electronics, 2020 - mdpi.com
Numerous works focus on the data privacy issue of the Internet of Things (IoT) when training
a supervised Machine Learning (ML) classifier. Most of the existing solutions assume that …
a supervised Machine Learning (ML) classifier. Most of the existing solutions assume that …
[HTML][HTML] Privacy-preserving distributed deep learning via homomorphic re-encryption
F Tang, W Wu, J Liu, H Wang, M **an - Electronics, 2019 - mdpi.com
The flourishing deep learning on distributed training datasets arouses worry about data
privacy. The recent work related to privacy-preserving distributed deep learning is based on …
privacy. The recent work related to privacy-preserving distributed deep learning is based on …
Efficient k-nearest neighbor classification over semantically secure hybrid encrypted cloud database
W Wu, J Liu, H Rong, H Wang, M **an - IEEE Access, 2018 - ieeexplore.ieee.org
Nowadays, individuals and companies increasingly tend to outsource their databases and
further data operations to cloud service provides. However, utilizing the cost-saving …
further data operations to cloud service provides. However, utilizing the cost-saving …
SecKNN: FSS-based secure multi-party KNN classification under general distance functions
Z Li, H Wang, S Zhang, W Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As a practical machine learning method, the K-nearest neighbors (KNN) classification has
received widespread attention. The achievement of the KNN classification relies heavily on …
received widespread attention. The achievement of the KNN classification relies heavily on …
Exploring the Existing and Unknown Side Effects of Privacy Preserving Data Mining Algorithms
HB Sadashiva Reddy - 2022 - nsuworks.nova.edu
The data mining sanitization process involves converting the data by masking the sensitive
data and then releasing it to public domain. During the sanitization process, side effects …
data and then releasing it to public domain. During the sanitization process, side effects …