信任开源信息

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI:10.1109/EISIC.2013.77

Marianela García Lozano

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引用次数: 0

摘要

情报分析依赖于来自可信和可靠来源的可信输入数据。开源信息(OSINF)提供了大量的数据，但它也带来了噪音的代价，即，许多数据是不相关的、模棱两可的、相互矛盾的、有偏见的或明显错误的。尽管如此，充分利用osinff所包含的丰富数据将提高情报分析的质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Trusting Open Source Information

Intelligence analysis is dependent on credible input data that comes from trusted and reliable sources. Open Source Information (OSINF) provides an abundance of data, but it comes with the price of noise, i.e., a lot of the data is irrelevant, ambiguous, contradicting, biased or plain wrong. Despite this, making full use of the wealth of data that OSINF encompasses would improve the quality of intelligence analysis.

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2013 European Intelligence and Security Informatics Conference

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