Image Steganalysis Method Based On Improved Smote And Focal Loss Algorithm
- DOI
- 10.2991/978-94-6463-058-9_66How to use a DOI?
- Keywords
- Image steganalysis; Unbalanced sample; Oversampling; SMOTE algorithm; Focal loss algorithm
- Abstract
Aiming at the performance degradation of steganalysis model caused by unbalanced sample data set training, a model design method based on improved SMOTE algorithm and Focal loss algorithm is proposed. The improved SMOTE algorithm is used to synthesize new samples to balance the data set. At the same time, the Focal loss algorithm is introduced to pay more attention to the difficult samples and optimize the training process of the model. In the simulation test of the model on BOSSbase1.01 data set, under the training of the unbalanced sample set, the detection rate is significantly higher than the similar Zhu-Net method, and the average detection rate is increased by 0.9%, up to 1.9%. This proves the effectiveness of this method and improves the accuracy of model detection.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haotian Zhao AU - Ke Niu AU - Zhiqiang Ning AU - Xiaozhong Pan PY - 2022 DA - 2022/12/27 TI - Image Steganalysis Method Based On Improved Smote And Focal Loss Algorithm BT - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) PB - Atlantis Press SP - 404 EP - 412 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-058-9_66 DO - 10.2991/978-94-6463-058-9_66 ID - Zhao2022 ER -