- 著者
- Shuang WANG Hui CHEN Lei DING He SUI Jianli DING
- 出版者
- The Institute of Electronics, Information and Communication Engineers
- 雑誌
- IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
- 巻号頁・発行日
- vol.E106-D, no.7, pp.1209-1218, 2023-07-01
- 被引用文献数
- 1
The issue of a low minority class identification rate caused by data imbalance in anomaly detection tasks is addressed by the proposal of a GAN-SR-based intrusion detection model for industrial control systems. First, to correct the imbalance of minority classes in the dataset, a generative adversarial network (GAN) processes the dataset to reconstruct new minority class training samples accordingly. Second, high-dimensional feature extraction is completed using stacked asymmetric depth self-encoder to address the issues of low reconstruction error and lengthy training times. After that, a random forest (RF) decision tree is built, and intrusion detection is carried out using the features that SNDAE retrieved. According to experimental validation on the UNSW-NB15, SWaT and Gas Pipeline datasets, the GAN-SR model outperforms SNDAE-SVM and SNDAE-KNN in terms of detection performance and stability.
- 著者
- Hiroki TAKAMURA Hiroshi KADOMURA Hidehiro SOHMA Norio TASE Hiromi HAMADA Yuichi SUZUKI Akihiko INAMURA Hiroshi SHIMAZU Payzulla ZAYDUN Tsuyoshi OHTA Masaya YASUHARA Tashpolat TIYIP Tadashi KONO Hamid YIMIT Heigang XIONG Wei ZHONG Heigang XIONG Nurbay ABDUSALIH Peipou HUANG Hiroyuki SAWADA Hiroshi UMEMURA Kentaro SUZUKI Gulmira OMAR Kunihiko ENDO Motoko KANEMAKI Xiaoyu MA Jianli DING Jianqian ZHAN
- 出版者
- The Association of Japanese Geographers
- 雑誌
- 地理学評論 (ISSN:13479555)
- 巻号頁・発行日
- vol.75, no.12, pp.750-761, 2002-10-01 (Released:2008-12-25)