Hyunbin Kim, Junchul Chun, Vol. 18, No. 8, August 31, 2024
10.3837/tiis.2024.08.013

• Anomaly Detection
• Image alignment
• PatchCore
• Semi-supervised learning
• Feature map hard masking

Seong-Mok Kim, Ye-Eun Jeong, Yong Soo Kim, Youn-Ho Lee, Seung Young Lee, Vol. 18, No. 5, May 31, 2024
10.3837/tiis.2024.05.009

• Weapon System
• Missile
• Quality Control
• Anomaly Detection
• Unsupervised learning

Kangseok Kim, Vol. 18, No. 2, February 29, 2024
10.3837/tiis.2024.02.012

• Anomaly Detection
• data augmentation
• Hybrid Approach
• NIDS
• Unsupervised Learning Technologies

Younghwa Lee, Il-Sik Chang, Suseong Oh, Youngjin Nam, Youngteuk Chae, Geonyoung Choi, Gooman Park, Vol. 17, No. 6, June 30, 2023
10.3837/tiis.2023.06.001

• Motor gearbox
• Operating sound
• Mel-spectrogram
• Anomaly Detection
• Normalizing Flow
• Hierarchical feature extraction

Wei Fang, Xuelei Jia, Wen Zhang, Victor S. Sheng, Vol. 17, No. 2, February 28, 2023
10.3837/tiis.2023.02.011

• Log anomaly detection
• Message Middleware
• Attention Mechanism
• Gate Recurrent Unit (GRU)

Byeong-Uk Jeon, Kyungyong Chung, Vol. 16, No. 8, August 31, 2022
10.3837/tiis.2022.08.018

• Anomaly Detection
• Multi Scale Feature Extraction
• Self-Supervised Learning

Mehmet Sevri, Hacer Karacan, Vol. 16, No. 2, February 28, 2022
10.3837/tiis.2022.02.014

• Anomaly Detection
• Deep Learning
• Ensemble learning
• web application firewall
• Web Security

Xue-Yong Yu, Xin-Hui Guo, Vol. 14, No. 10, October 31, 2020
10.3837/tiis.2020.10.004

• Incremental Principal Component Analysis
• Offline and real-time learning
• Fog Computing
• Data anomaly detection

Xinqian Liu, Jiadong Ren, Haitao He, Qian Wang, Shengting Sun, Vol. 14, No. 7, July 31, 2020
10.3837/tiis.2020.07.020

• Network Anomaly Detection
• data balancing
• recursive feature addition
• parameters combination optimization
• random forests

Sasan Saqaeeyan, Hamid Haj Seyyed javadi, Hossein Amirkhani, Vol. 14, No. 4, April 30, 2020
10.3837/tiis.2020.04.021

• Smart Homes
• Sensory data
• Anomaly Detection
• Bayesian networks