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In conclusion, we have developed a system that integrates data analysis, machine learning, manual labeling, TFIDF weighting techniques, and a malicious score. The use of K-means algorithms and MITRE ATT&CK TTP tags allows for quick identification of high-threat attacks, which is valuable for further research. Furthermore, dividing large-scale attacks into smaller groups helps with data labeling, enabling systematic categorization and storage of data as Session Table. Although the proposed system achieved a clustering accuracy of 99.5%, and the source is labeled to provide a reliable dataset with realistic examples, the experiments in this study are not applicable to other situations. |
IEEE/ICACT20230048 Slide.21
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