Random Forest Stratified K-Fold Cross Validation on SYN DoS Attack SD-IoV

• URL: http://arxiv.org/abs/2509.07016v1
• Date: Sun, 07 Sep 2025 00:18:30 GMT
• Title: Random Forest Stratified K-Fold Cross Validation on SYN DoS Attack SD-IoV
• Authors: Muhammad Arif Hakimi Zamrai, Kamaludin Mohd Yusof,
• Abstract summary: TCP SYN flood attacks are prevalent within the context of Software-Defined Internet of Vehicles (SD-IoV)<n>This research focuses on optimizing a Random Forest model to achieve maximum accuracy and minimal detection time.<n>It provides a robust solution against TCP SYN flood attacks while maintaining network efficiency and reliability.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In response to the prevalent concern of TCP SYN flood attacks within the context of Software-Defined Internet of Vehicles (SD-IoV), this study addresses the significant challenge of network security in rapidly evolving vehicular communication systems. This research focuses on optimizing a Random Forest Classifier model to achieve maximum accuracy and minimal detection time, thereby enhancing vehicular network security. The methodology involves preprocessing a dataset containing SYN attack instances, employing feature scaling and label encoding techniques, and applying Stratified K-Fold cross-validation to target key metrics such as accuracy, precision, recall, and F1-score. This research achieved an average value of 0.999998 for all metrics with a SYN DoS attack detection time of 0.24 seconds. Results show that the fine-tuned Random Forest model, configured with 20 estimators and a depth of 10, effectively differentiates between normal and malicious traffic with high accuracy and minimal detection time, which is crucial for SD-IoV networks. This approach marks a significant advancement and introduces a state-of-the-art algorithm in detecting SYN flood attacks, combining high accuracy with minimal detection time. It contributes to vehicular network security by providing a robust solution against TCP SYN flood attacks while maintaining network efficiency and reliability.

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