A Non-genuine Message Detection Method Based on Unstructured Datasets

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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.




Trovati, M., Hill, R., & Bessis, N. (2015). A Non-genuine Message Detection Method Based on Unstructured Datasets. In Proceedings - 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2015 (pp. 597–600). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/3PGCIC.2015.108

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