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Human-Machine Interaction Technology (HIT)

Performance Comparison According to Image Generation Method in NIDS (Network Intrusion Detection System) using CNN

초록

영어

Recently, many studies have been conducted on ways to utilize AI technology in NIDS (Network Intrusion Detection System). In particular, CNN-based NIDS generally shows excellent performance. CNN is basically a method of using correlation between pixels existing in an image. Therefore, the method of generating an image is very important in CNN. In this paper, the performance comparison of CNN-based NIDS according to the image generation method was performed. The image generation methods used in the experiment are a direct conversion method and a one-hot encoding based method. As a result of the experiment, the performance of NIDS was different depending on the image generation method. In particular, it was confirmed that the method combining the direct conversion method and the one-hot encoding based method proposed in this paper showed the best performance.

목차

Abstract
1. Introduction
2. Materials and Methods
2.1 NSL-KDD Dataset
2.2 Image Generation Based on Direct Conversion
2.3 Image Generation Based on One-Hot Encoding
3. Proposed Method for Performance Comparison
4. Results and Discussion
5. Conclusion
Acknowledgement
References

저자정보

  • Sang Hyun, Kim Professor, Department of Cyber Security, Youngsan University, Yangsan Campus

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