一种基于非结构化数据集的非真实消息检测方法

2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC) Pub Date : 2015-11-04 DOI:10.1109/3PGCIC.2015.108

M. Trovati, Richard Hill, N. Bessis

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引用次数: 4

摘要

由于网络罪犯使用的技术不断变化，对非真实或恶意信息的识别提出了各种挑战。在本文中，我们讨论了[1]中引入的文本垃圾识别方法的进一步评估，该方法基于文档的语义属性来评估恶意程度。进一步的实验结果表明了该方法的准确性和潜力。

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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A Non-genuine Message Detection Method Based on Unstructured Datasets

The identification of non-genuine or malicious messages poses a variety of challenges due to the continuous changes in the techniques utilised by cyber-criminals. In this article, we discuss a further evaluation of the text spam recognition method introduced in [1], which is based on semantic properties of documents to assess the level of maliciousness. Further experimental results show the accuracy and potential of our approach.

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来源期刊

2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)

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