Frequent item set mining method for local differential privacy protection based on singular value decomposition
A technology of frequent itemset mining and singular value decomposition, applied in the field of information security, can solve the problems of increased noise and increased communication overhead, and achieve the effect of reducing communication overhead and accurate mining results
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0039] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention, and the schematic embodiments and descriptions of the present invention are used to explain the present invention, and do not constitute an improper limitation of the present invention.
[0040] Based on the local differential privacy framework, the present invention proposes a brand-new mining method for private frequent itemsets, which can perform an optimal trade-off between data privacy, mining precision, and communication overhead. The basic idea is: firstly, on the distributed client side, use the low-dimensional singular value matrix to represent the user’s original high-dimensional sensitive data matrix; secondly, on the server side, collect insensitive singular values and restore them to finally obtain frequent itemsets An accurate estimate of the group.
[0041] Such as figure 1 The illustrated embodiment provides a frequent itemset ...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com