Сlassification methodology e-mails using neural networks
DOI:
https://doi.org/10.18372/2410-7840.15.4775Keywords:
email, spam, leakage, neural networks, Kohonen mapAbstract
The effectiveness of email security is largely dependent on the accuracy of spam detection in leaves and roots. Existing recognition methods based on statistical analysis of text information, which significantly limits their ability to detect new types of spam and leaks. To overcome this shortcoming proposed classification methodology sheets based on semantic analysis using an electronic neural networks. A used as input parameters of the neural network in the frequency of meeting the letter of informative words in canonical form. It is shown that the best type of neural network model is Kohonen map, the main advantage of which is a high-speed training and the possibility of easy visualization of classification. This allows you to quickly react to new spam and howl leaks and conduct a final classification of letters by the user. The experiments confirmed the possibility of increasing the reliability of detection of 20-30%References
Заболеева-Зотова А.В. Естественный язык в автоматизированных системах. Семантический анализ текстов / А.В. Заболеева-Зотова. – Волгоград : ВолгГТУ, 2002. – 228 с.
Зиновьев А.Ю. Визуализация многомерных даннях / А. Ю. Зиновьев. - М. : СК Пресс, 2005. - 180 с.
Ежов А. А. Нейрокомпьютинг и его применения в экономике и бизнесе / А. А. Ежов, С. А. Шумский. - М. : МИФИ, 1998. - 224 с.
Терейковський И. А. Применение семантического анализа содержимого электронных писем в системах распознавания спама / И. А. Терейковский // Захист інформації. – 2006. - № 4. – С. 49-60.
Терейковський І.А. Оптимізація архітектури нейронної мережі призначеної для діагностики стану комп’ютерної мереж / І. А. Терейковський // Наук.-техн. зб. Управління розвитком складних систем Київського національного університету будівництва і архітектури. – 2011. – Випуск 6. – С. 155-158.
Zaboleeva-A.V. Zotova Natural language in automated systems. Semantic text analysis / A. Zaboleeva-Zotov., Volgograd Volgograd State Technical University, 2002, 228 p.
Zinoviev A. Visualization of multidimensional dannyah, M. SK Press, 2005, 180 р.
Yezhov A. A. Neurocomputing and its applications in economics and business / A.A. Ezhov, SA Shumsky.,Moscow Engineering Physics Institute, 1998, 224 р.
Tereykovskiy I. A. application of semantic analysis of the content of emails in spam detection systems Zahist іnformatsії, 2006, № 4, Р. 49-60.
Tereykovskiy I. A. Optimization of neural network architecture designed to diagnose the state of the computer networking, Scientific and Technical. Collected. Management of complex systems Kyiv National University of Construction and Architecture, 2011, Release 6, Р. 155-158.
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