Сетевая криминалистика помогает выследить кибермошенников путем оценки и отслеживания сетевых данных. Сетевая криминалистика - это анализ сетевого трафика для обнаружения вторжений и изучения того, как произошло преступление, т.е. создание места преступления для расследования и воспроизведения. В данном исследовании предлагается общая модель и архитектура процесса сетевой криминалистики. Для анализа используется вторичный набор данных KDD CUP с нормальным и аномальным трафиком, чтобы смоделировать весь процесс. Набор данных в значительной степени обрабатывается для отбора признаков и удаления избыточности. Набор данных был очищен перед анализом с помощью модели обучения Support Vector Machine для классификации трафика. Многоклассовая классификация была использована для классификации различных типов сетевых атак. Точность модели оценивается по полученным результатам.

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