Towards secure big data analytic for cloud-enabled applications with fully homomorphic encryption
Cloud computing empowers enterprises to efficiently manage big data and discovery of
useful information which are the most fundamental challenges for big data enabled …
useful information which are the most fundamental challenges for big data enabled …
Practical privacy-preserving k-means clustering
Clustering is a common technique for data analysis, which aims to partition data into similar
groups. When the data comes from different sources, it is highly desirable to maintain the …
groups. When the data comes from different sources, it is highly desirable to maintain the …
Sok: Efficient privacy-preserving clustering
Clustering is a popular unsupervised machine learning technique that groups similar input
elements into clusters. It is used in many areas ranging from business analysis to health …
elements into clusters. It is used in many areas ranging from business analysis to health …
Privacy-preserving federated k-means for proactive caching in next generation cellular networks
Proactive caching is a novel smart communication resource management method that can
offer intelligent and economic networking services in the next generation cellular networks …
offer intelligent and economic networking services in the next generation cellular networks …
Privacy preserving distributed k-means clustering in malicious model using zero knowledge proof
Preserving Privacy is crucial in distributed environments wherein data mining becomes a
collaborative task among participants. Solutions proposed on the lines of cryptography …
collaborative task among participants. Solutions proposed on the lines of cryptography …
Efficient two-party privacy-preserving collaborative k-means clustering protocol supporting both storage and computation outsourcing
Nowadays, cloud computing has developed well and been applied in many kinds of areas.
However, privacy is still the most challenging problem which obstructs it being applied in …
However, privacy is still the most challenging problem which obstructs it being applied in …
Sparse dual graph-regularized NMF for image co-clustering
Nonnegative matrix factorization (NMF) as fundamental technique for clustering has been
receiving more and more attention. This is because it can effectively reduce high …
receiving more and more attention. This is because it can effectively reduce high …
A hybrid active contour model based on global and local information for medical image segmentation
L Fang, T Qiu, H Zhao, F Lv - Multidimensional Systems and Signal …, 2019 - Springer
For segmenting medical images with abundant noise, blurry boundaries, and intensity
heterogeneities effectively, a hybrid active contour model that synthesizes the global …
heterogeneities effectively, a hybrid active contour model that synthesizes the global …
Privacy-preserving anomaly detection in the cloud for quality assured decision-making in smart cities
Rapid urbanisation places extensive demands on city services and infrastructure that
mandate innovative and sustainable solutions which increasingly involve streamlined …
mandate innovative and sustainable solutions which increasingly involve streamlined …
Privacy-preserving distributed clustering for electrical load profiling
Electrical load profiling supports retailers in identifying consumer categories for customizing
tariff design. However, each retailer only has access to the data of the customers it serves …
tariff design. However, each retailer only has access to the data of the customers it serves …