Digital Library

1. 1. A Study on Data Augmentation Methods for Improving the Performance of Machine Learning Models in Network Attack Detection
   Taesu Kim, Dongkyoo Shin, Dongil Shin, Vol. 26, No. 3, pp. 1-7, Jun. 2025
   10.7472/jksii.2025.26.3.1
   Keywords: Network intrusion detection, data augmentation
2. 2. Research on Network Packet Analysis and Unknown Intrusion Detection Method based on LSTM-Autoencoder
   Hyoseong Park, Dongkyoo Shin, Dongil Shin, Vol. 26, No. 1, pp. 149-155, Feb. 2025
   10.7472/jksii.2025.26.1.149
   Keywords: LSTM, Autoencoder, Network intrusion detection, CIC-IDS2018
3. 3. A Research on Network Intrusion Detection based on Discrete Preprocessing Method and Convolution Neural Network
   JiHoon Yoo, Byeongjun Min, Sangsoo Kim, Dongil Shin, Dongkyoo Shin, Vol. 22, No. 2, pp. 29-39, Apr. 2021
   10.7472/jksii.2021.22.2.29
   Keywords: NSL-KDD, Network intrusion detection, CNN, Discretization of Continuous
4. 4. Network Intrusion Detection with One Class Anomaly Detection Model based on Auto Encoder
   Byeoungjun Min, Jihoon Yoo, Sangsoo Kim, Dongil Shin, Dongkyoo Shin, Vol. 22, No. 1, pp. 13-22, Feb. 2021
   10.7472/jksii.2021.22.1.13
   Keywords: Anomaly Detection, Network intrusion detection, Autoencoder, NSL-KDD
5. 5. Deep Learning-based Abnormal Behavior Detection System for Dementia Patients
   Kookjin Kim, Seungjin Lee, Sungjoong Kim, Jaegeun Kim, Dongil Shin, Dong-kyoo shin, Vol. 21, No. 3, pp. 133-144, Jun. 2020
   10.7472/jksii.2020.21.3.133
   Keywords: Abnomaly detection, deep-learning, Autoencoder, Long Short-Term Memory models
6. 6. A Study on the Operation Concept of Cyber Warfare Execution Procedures
   Sung-Joong Kim, JiHoon Yoo, HaengRok Oh, Dongil Shin, DongKyoo Shin, Vol. 21, No. 2, pp. 73-80, Apr. 2020
   10.7472/jksii.2020.21.2.73
   Keywords: cyber warfare, Battle damage assessment
7. 7. A research on the emotion classification and precision improvement of EEG(Electroencephalogram) data using machine learning algorithm
   Hyunju Lee, Dongil Shin, Dongkyoo Shin, Vol. 20, No. 5, pp. 27-36, Oct. 2019
   10.7472/jksii.2019.20.5.27
   Keywords: DEAP dataset, ICA, Arousal-Valence plane, Random Forest, Attribute Selected Classifier