Digital Library

1. 61. A Study on Methods for Accelerating Sea Object Detection in Smart Aids to Navigation System
   Ho-Seok Jeon, Hyun-hak Song, Ki-Won Kwon, Young-Jin Kim, Tae-Ho Im, Vol. 23, No. 5, pp. 47-58, Oct. 2022
   10.7472/jksii.2022.23.5.47
   Keywords: Maritime Object detection, motion detection, image processing, Aids to Navigation, Protection of Safety Accidents
2. 62. Deep Learning Based Rescue Requesters Detection Algorithm for Physical Security in Disaster Sites
   Da-hyeon Kim, Man-bok Park, Jun-ho Ahn, Vol. 23, No. 4, pp. 57-64, Aug. 2022
   10.7472/jksii.2022.23.4.57
   Keywords: Risk of building, Physical Security, Deep Learning, Disaster sites, Object Detection
3. 63. A Study on the Evaluation of Classification Performance by Capacity of Explosive Components using Convolution Neural Network (CNN)
   Chang-Hyeon Lee, Sung-Yoon Cho, Ki-Won Kwon, Tae-Ho Im, Vol. 23, No. 4, pp. 11-19, Aug. 2022
   10.7472/jksii.2022.23.4.11
   Keywords: Deep Learning, explosive classification, abnormality detection system
4. 64. Analysis of Building Characteristics and Temporal Changes of Fire Alarms
   Gwanmuk Lim, Seoltae Ko, Yoosin Kim, Keon Chul Park, Vol. 22, No. 4, pp. 83-98, Aug. 2021
   10.7472/jksii.2021.22.4.83
   Keywords: Fire-fighting Facility Management System, Automatic Fire Detection Facility, Fire Alarm, Fire Detector, Real-time Sensing Analysis
5. 65. A hybrid intrusion detection system based on CBA and OCSVM for unknown threat detection
   Gun-Yoon Shin, Dong-Wook Kim, Jiyoung Yun, Sang-Soo Kim, Myung-Mook Han, Vol. 22, No. 3, pp. 27-35, Jun. 2021
   10.7472/jksii.2021.22.3.27
   Keywords: Unknown Threat, Hybrid Intrusion Detection, Classification based on Association Rule, One-class SVM
6. 66. Intelligent Abnormal Situation Event Detections for Smart Home Users Using Lidar, Vision, and Audio Sensors
   Da-hyeon Kim, Jun-ho Ahn, Vol. 22, No. 3, pp. 17-26, Jun. 2021
   10.7472/jksii.2021.22.3.17
   Keywords: Smart home. Intelligent, Abnormal detections, Sensor fusing, algorithm
7. 67. Application of Discrete Wavelet Transforms to Identify Unknown Attacks in Anomaly Detection Analysis
   Dong-Wook Kim, Gun-Yoon Shin, Ji-Young Yun, Sang-Soo Kim, Myung-Mook Han, Vol. 22, No. 3, pp. 45-52, Jun. 2021
   10.7472/jksii.2021.22.3.45
   Keywords: Unknown Attack, Discrete wavelet transform, Anomaly Detection, One-class SVM
8. 68. 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
9. 69. An Interpretable Log Anomaly System Using Bayesian Probability and Closed Sequence Pattern Mining
   Jiyoung Yun, Gun-Yoon Shin, Dong-Wook Kim, Sang-Soo Kim, Myung-Mook Han, Vol. 22, No. 2, pp. 77-87, Apr. 2021
   10.7472/jksii.2021.22.2.77
   Keywords: Explainable AI, Log anomaly detection, Bayesian Probability, Rule Extraction
10. 70. 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