SUKRY: Suricata IDS with Enhanced kNN Algorithm on Raspberry Pi for Classifying IoT Botnet Attacks
نویسندگان
چکیده
The focus of this research is the application k-Nearest Neighbor algorithm in terms classifying botnet attacks IoT environment. kNN has several advantages classification tasks, such as simplicity, effectiveness, and robustness. However, it does not perform well handling large datasets Bot-IoT dataset, which represents a huge amount data about on networks. Therefore, improving performance main concern study by applying feature selection techniques. whole process was conducted Rapidminer environment using three prebuilt techniques, namely, Information Gain, Forward Selection, Backward Elimination. After comparing accuracy, precision, recall, F1 score processing time, combination Selection technique (kNN-FS) achieves best results among others, with highest level accuracy fastest execution time others. Finally, kNN-FS used developing SUKRY, stands for Suricata IDS Enhanced Algorithm Raspberry Pi.
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ژورنال
عنوان ژورنال: Electronics
سال: 2022
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics11050737