A comprehensive survey on secure outsourced computation and its applications

Y Yang, X Huang, X Liu, H Cheng, J Weng, X Luo… - IEEE …, 2019‏ - ieeexplore.ieee.org
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 …

K-means clustering and kNN classification based on negative databases

D Zhao, X Hu, S **ong, J Tian, J **ang, J Zhou… - Applied soft computing, 2021‏ - Elsevier
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 …

{SANNS}: Scaling up secure approximate {k-Nearest} neighbors search

H Chen, I Chillotti, Y Dong, O Poburinnaya… - 29th USENIX Security …, 2020‏ - usenix.org
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 …

Motor imagery based brain-computer interface: improving the EEG classification using Delta rhythm and LightGBM algorithm

S Abenna, M Nahid, A Bajit - Biomedical Signal Processing and Control, 2022‏ - Elsevier
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 …

Toward highly secure yet efficient KNN classification scheme on outsourced cloud data

L Liu, J Su, X Liu, R Chen, K Huang… - IEEE Internet of …, 2019‏ - ieeexplore.ieee.org
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 …

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 …

[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 …

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 …

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 …

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 …