{
  "patent_number": "US 20250184362",
  "country": "US",
  "title": "Securely Analyzing Mixed Data with Distributed AI and Privacy",
  "original_title": "Federated mining method and system for multimodal data based on multiple security policies",
  "summary": "This patent describes a method for securely analyzing different types of data, like images and text, across multiple computers without collecting all the data in one place, while also protecting privacy.",
  "what_it_does": "This patent outlines a method for analyzing diverse data, known as multimodal data, using a distributed approach called federated learning (S1). It sets up a system where multiple computers, called local edge nodes, can work together on data without sharing the raw information. Before participating, each node undergoes a 'multiple authentication mechanism' (S2), which includes a lightweight trusted verification using a random forest model and a calculation of its 'local model reputation' based on its F1_score and error rate. The system then performs 'multimodal data fusion' and 'multimodal data classification' on the combined dataset using a 'generalized multimodal data feature fusion model' that relies on a 'multi-head attention mechanism' (S3). This mechanism involves extracting features (e.g., 3D-CNN for images, OpenSmile for audio, Word2Vec for text), splicing them, calculating correlation scores, and using these scores to weight and sum representations for fusion and dimensionality reduction. Finally, an 'adaptive perturbation mechanism' (S4) adds noise dynamically to protect privacy, using cyclic correlation analysis and differential privacy with Gaussian noise.",
  "what_it_does_not_cover": [
    "Does not cover data mining systems that collect all raw data into a central location before processing.",
    "Does not cover systems that rely on only a single method for verifying the trustworthiness of participating data nodes.",
    "Does not cover analysis of data that consists of only one type, such as just images or just audio.",
    "Does not cover privacy protection methods that add noise without dynamically adjusting it based on data correlations and differential privacy.",
    "Does not cover data fusion models that do not specifically use a multi-head attention mechanism for combining different data types."
  ],
  "filed": "2024-12-30",
  "granted": null,
  "expires": "2044-12-30",
  "status": "active",
  "holder": "Xuzhou Medical College",
  "holder_url": "https://patentbrief.org/company/xuzhou-medical-college",
  "inventors": [
    {
      "name": "Lili Wang",
      "url": "https://patentbrief.org/inventor/lili-wang"
    },
    {
      "name": "Chuanchuan LU",
      "url": "https://patentbrief.org/inventor/chuanchuan-lu"
    },
    {
      "name": "Xiang Wu",
      "url": "https://patentbrief.org/inventor/xiang-wu"
    },
    {
      "name": "Dianlei HU",
      "url": "https://patentbrief.org/inventor/dianlei-hu"
    },
    {
      "name": "Yongting ZHANG",
      "url": "https://patentbrief.org/inventor/yongting-zhang"
    }
  ],
  "times_cited": 14,
  "tags": [
    "biotech",
    "software",
    "telecommunications",
    "ai_ml",
    "consumer_electronics"
  ],
  "abstract": "A federated mining method for multimodal data based on multiple security policies includes: a federated learning framework is used as a data mining model for distributed data mining; a multiple authentication mechanism is designed; a local edge node is selected to participate in a federated computation to obtain authenticated local edge node and aggregate a dataset; a multimodal data fusion and a multimodal data classification are performed on the dataset by a generalized multimodal data feature fusion model based on a multi-headed attention mechanism; and an adaptive perturbation mechanism based on cyclic correlation analysis and differential privacy is designed to add noise round by round and dynamically. A federated mining method for multimodal data is further provided.",
  "url": "https://patentbrief.org/patent/us/20250184362/federated-mining-method-and-system-for-multimodal-data-based-on-multiple-securit",
  "markdown_url": "https://patentbrief.org/patent/us/20250184362/federated-mining-method-and-system-for-multimodal-data-based-on-multiple-securit/md",
  "google_patents_url": "https://patents.google.com/patent/US20250184362",
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}