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ATTRIBUTION – DATA- ANALYSIS – COUNTERMEASURES – INTEROPERABILITY: ADAC.IO

ATTRIBUTION – DATA- ANALYSIS – COUNTERMEASURES – INTEROPERABILITY: ADAC.IO
归因 – 数据分析 – 对策 – 互操作性:ADAC.IO
批准号:
10105669
负责人:
金额:
$32.67万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

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中文摘要
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英文摘要
The purpose of this project is to protect democracy in the EU by strengthening the ability to deny the intended effects of FIMI on society. This will be achieved with focused research that brings together some of the principal actors behind the intellectual and technical components of FIMI as it has been developed by the EEAS and other EU Institutions. We will work together to significantly develop upon current knowledge of how FIMI can be detected, categorised, analysed, shared, and countered. We will achieve this through a series of coordinated contributions to the DISARM Framework, the NATO-Hybrid COE Attribution Framework, STIX 2.1, OpenCTI, ABCDE, and the FIMI countermeasures toolbox. This approach acknowledges the importance of TTPs and common data handling standards to the ability to attribute FIMI actors, and further positions TTPs within the broader analytical processes that are necessary to developing countermeasures. In addition to establishing improved technical standards and operating procedures, we will generate research knowledge that can support better decision-making about FIMI countermeasures. For example, we will conduct research into the public impact of attribution, research methods for linguistic and visual analysis, develop the understanding of how cross-platform manipulation evades traditional analysis methods, as well as establishing a dataset of previous FIMI interventions. We include a specific component on gendered disinformation designed to better integrate gender into the technical formats. Finally, we will work closely with a community of practice that includes the EEAS, representatives of member states, civil society, and journalists/EDMO.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: