The study introduces IG, a mechanism that leverages coherent patterns to enhance intrusion detection systems. By analyzing real-world datasets, IG achieves high precision, recall, and AUC scores across diverse scenarios. The method's interpretability and reproducibility make it a valuable asset in cybersecurity defense.
The content delves into the challenges faced by traditional IDS systems and the importance of explainable AI methodologies in enhancing system performance. The authors highlight the significance of coherent pattern recognition in identifying novel anomalies without prior exposure. Through experiments with NSL-KDD, UNSW-NB15, and UKM-IDS20 datasets, IG showcases superior generalization capabilities.
Furthermore, the study compares IG's performance with other methods in terms of accuracy, recall, precision, and AUC across different datasets. The results demonstrate IG's effectiveness in accurately detecting anomalies while minimizing false alarms. Overall, IG stands out as a reliable and interpretable solution for cybersecurity forensics.
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arxiv.org
ข้อมูลเชิงลึกที่สำคัญจาก
by Hao-Ting Pai... ที่ arxiv.org 03-14-2024
https://arxiv.org/pdf/2403.07959.pdfสอบถามเพิ่มเติม