RECENT & SELECTED PUBLICATIONS

MultiSHTM: Multi-Level Attention Enabled Bi-Directional Model for the Summarization of Chart Images (2025)

Indra Kumari and Hansung Lee, IEEE ACCESS [SCIE, IF 3.4, JCR Q2] , vol. 13, p. 101789 - 101800, June. 2025, doi: 10.1109/ACCESS.2025.3568849. [Online]. Available: https://ieeexplore.ieee.org/document/11000319

Abstract(Short): Chart-to-text conversion is an emerging research area focused on extracting useful information from chart images to improve understanding and analysis. We propose a new method called MultiSHTM (Multi-level Stacked Houghless Network-based Bi-LSTM). This method improves accuracy, reduces complexity, and works well across different chart types. MultiSHTM integrates two key innovations: 1) a multilevel attention mechanism in a stacked houghless network, which accurately identifies key points in charts without relying on traditional Hough Transform-based methods and 2) a Bi-LSTM model enhanced with a Hierarchical and Channel Attention module, which effectively captures contextual relationships to generate precise summaries of chart images.

The Amalgamation of the Object Detection and Semantic Segmentation for Steel Surface Defect Detection (2022)

M. Sharma, J. Lim, and H. Lee, Applied Sciences [SCIE, IF 2.679, JCR Q2] , vol. 12, no. 12, p. 6004, Jun. 2022, doi: 10.3390/app12126004. [Online]. Available: http://dx.doi.org/10.3390/app12126004

Abstract(Short): To resolve the atypical defects problem, we introduce a hierarchical approach for the classification and detection of defects on the steel surface. The proposed approach has a hierarchical structure of the binary classifier at the first stage and the object detection and semantic segmentation algorithms at the second stage. It shows 98.6% accuracy in scratch and other types of defect classification and 77.12% mean average precision (mAP) in defect detection using the Northeastern University (NEU) surface defect detection dataset.

AI-Based Stroke Disease Prediction System Using ECG and PPG Bio-Signals (2022)

J. Yu, S. Park, S. -H. Kwon, K. -H. Cho and H. Lee, IEEE Access [SCIE, IF 3.367, JCR Q1], vol. 10, pp. 43623-43638, 2022, doi: 10.1109/ACCESS.2022.3169284.
[Online]. Available: http://dx.doi.org/10.1109/ACCESS.2022.3169284

Abstract(Short): We propose a system that can predict and semantically interpret stroke prognostic symptoms based on machine learning using the multi-modal bio-signals of electrocardiogram (ECG) and photoplethysmography (PPG) measured in real-time for the elderly. To predict stroke disease in real-time while walking, we designed and implemented a stroke disease prediction system with an ensemble structure that combines CNN and LSTM. According to the experimental results, C4.5 decision tree showed a prediction accuracy of 91.56% while RandomForest showed a prediction accuracy of 97.51% during walking by the elderly. In addition, the CNN-LSTM model using raw data of ECG and PPG showed satisfactory prediction accuracy of 99.15%.

Attack Graph Generation with Machine Learning for Network Security (2022)

K. Koo, D. Moon, J.-H. Huh, S.-H. Jung, and H. Lee, Electronics [SCIE, IF 2.397, JCR Q2], vol. 11, no. 9, p. 1332, Apr. 2022, doi: 10.3390/electronics11091332.
[Online]. Available: http://dx.doi.org/10.3390/electronics11091332

Abstract(Short): We propose a cheap and simple method for generating the attack graph. The proposed approach consists of learning and generating stages. First, it learns how to generate an attack path from the attack graph, which is created based on the vulnerability database, using machine learning and deep learning. Second, it generates the attack graph using network topology and system information with a machine learning model that is trained with the attack graph generated from the vulnerability database. The attack graph generation problem is recast as a multi-output learning and binary classification problem. It shows attack path detection accuracy of 89.52% in the multi-output learning approach and 80.68% in the binary classification approach using the in-house dataset, respectively.

Data Clustering Method Using a Modified Gaussian Kernel Metric and Kernel PCA (2014)

H. Lee, J. Yoo, and D. Park, ETRI Journal [SCIE, IF 1.4, JCR Q4], vol. 36, issue. 3, pp. 333-342, doi: 10.4218/etrij.14.0113.0553 [Online]. Available: https://doi.org/10.4218/etrij.14.0113.0553

Abstract(Short): Most hyper-ellipsoidal clustering (HEC) approaches use the Mahalanobis distance as a distance metric. It has been proven that HEC, under this condition, cannot be realized since the cost function of partitional clustering is a constant. We demonstrate that HEC with a modified Gaussian kernel metric can be interpreted as a problem of finding condensed ellipsoidal clusters and propose a practical HEC algorithm that is able to efficiently handle clusters that are ellipsoidal in shape and that are of different size and density. We then try to refine the HEC algorithm by utilizing ellipsoids defined on the kernel feature space to deal with more complex-shaped clusters.

PUBLICATIONS

▣ Master Thesis and PhD Dissertation

Master Thesis : The real-time IDS based on incremental clustering algorithm : design and implementation of Kernel-ART, Supervised by Prof. Daihee Park, 2002.
PhD Dissertation : A Data Cube System for the Semantic Analysis of News Video, Supervised by Prof. Daihee Park, 2008.

▣ International Journal

Indra Kumari and Hansung Lee. MultiSHTM: Multi-Level Attention Enabled Bi-Directional Model for the Summarization of Chart Images. IEEE Access. vol. 13, pp. 101789 - 101800, 2025. [SCIE]
Sharma, M.; Lim, J.; Lee, H. The Amalgamation of the Object Detection and Semantic Segmentation for Steel Surface Defect Detection. Appl. Sci. 2022, 12, 6004. [SCIE]
J.Yu, S.Park, S.-H.Kwon, K.-H. Cho and H. Lee, "AI-based Stroke Disease Prediction System using ECG and PPG Bio-signals," IEEE Access, vol. 10, pp. 43623-43638, April 2022. [SCIE]
Koo, K.; Moon, D.; Huh, J.-H.; Jung, S.-H.; Lee, H. Attack Graph Generation with Machine Learning for Network Security. Electronics 2022, 11, 1332. [SCIE]
Park,J.; Kim,J.-Y.; Huh,J.-H.; Lee,H.-S.; Jung,S.-H.; Sim,C.-B. A Novel on Conditional Min Pooling and Restructured Convolutional Neural Network. Electronics 2021,10,2407 [SCIE]
Choi, Y.; Park, S.; Jun, J.; Pyo, C..; Cho, K..; Lee, H.; Yu, J. Deep Learning-Based Stroke Disease Prediction System Using Real-Time Bio Signals. Sensors 2021, 21, 4269. [SCIE]
Choi, Y.; Park, S.; Jun, J..; Ho, C.; Pyo, C.; Lee, H.; Yu, J. Machine-Learning-Based Elderly Stroke Monitoring System Using Electroencephalography Vital Signals. Appl. Sci. 2021, 11, 1761. [SCIE]
Yu, J.; Park, S.; Kwon, S.; Ho, C.; Pyo, C.; Lee, H. AI-Based Stroke Disease Prediction System Using Real-Time Electromyography Signals. Appl. Sci. 2020, 10, 6791. [SCIE]
S. Jung, H. Lee, J. Huh. A Novel Model on Reinforce K-Means Using Location Division Model and Outlier of Initial Value for Lowering Data Cost. Entropy 2020, 22, 902. [SCIE]
Yu, J.; Park, S.; Lee, H.; Pyo, C.-S.; Lee, Y. An Elderly Health Monitoring System Using Machine Learning and In-Depth Analysis Techniques on the NIH Stroke Scale. Mathematics 2020, 8, 1115. [SCIE]
Lee, H.; Park, S.-H.; Yoo, J.-H.; Jung, S.-H.; Huh, J.-H. Face Recognition at a Distance for a Stand-Alone Access Control System. Sensors 2020, 20, 785. [SCIE]
J. Kwon and H. Lee, “Visual Tracking Based on Edge Field with Object Proposal Association,” Image and Vision Computing, vol. 69, pp. 22-32, 2018. [SCI]
H. Lee, D. Moon, I. Kim, H. Jung, D. Park, “Anomaly Intrusion Detection Based on Hyper-ellipsoid in the Kernel Feature Space,” TIIS, vol. 9, no. 3, pp. 1173-1192, 2015. [SCIE]
S. Park, H. Lee, J. Yoo, G. Kim, and S. Kim, "Partially Occluded Facial Image Retrieval Based on a Similarity Measurement," Math. Prob. in Eng., vol. 1, pp. 1-11. 2015. [SCIE]
H. Lee, J. Yoo, and D. Park, “A Data Clustering using the Modified Gaussian Kernel Metric and the Kernel PCA,” ETRI Journal, vol.36, no.3, pp.333-342, 2014. [SCI]
Y. Chung, H. Kim, H. Lee, D. Park, T. Jeon and H. Chang, “A Cost-Effective Pigsty Monitoring System Based on a Video Sensor,” TIIS, vol. 8, no. 4, pp. 1481-1498, 2014. [SCIE]
H.Lee, J.Yu, Y.Im, J.Gil, D.Park, “A Unified Scheme of Shot Boundary Detection and Anchor Shot Detection in News Video Story Parsing,” MULTI. TOOLS & APPL., vol.51, no.3, pp.1127-1145, 2011. [SCIE]
J.Yu, H.Lee, Y.Im, M.Kim, and D.Park,“Real-time Classification of Internet Application Traffic using a Hierarchical Multi-class SVM,”TIIS, vol.4, no.5, pp.859-876,2010. [SCIE]
Y. Im, S. Oh, M. Chung, J. Yu, H. Lee, J. Chang, and D. Park, “A KFD web database system with an object-based image retrieval for family art therapy assessments,” The Arts in Psychotherapy, vol. 37, no. 3, pp. 163-171, 2010. [SSCI]
J. Yu, H. Lee, M. Kim, and D. Park, “Traffic Flooding Attack Detection with SNMP MIB using SVM,” Comp. Comm. Journal, vol.31, no. 17, pp. 4212-4219, 2008. [SCIE]

▣ Lecture Notes (LNCS/LNAI)

H. Lee, Y. Chung, J. Kim, and D. Park, “Face Image Retrieval using Sparse Representation Classifier with Gabor-LBP Histogram,” WISA, vol. 6513, pp. 273-280, 2010. [LNCS]
H. Lee, Y. Chung, and D. Park, “An Adaptive Intrusion Detection Algorithm based on Clustering and Kernel-Method,” PAKDD, LNAI, vol. 3918, pp. 603-610, 2006. [LNAI/SCIE]
H. Lee, J. Song, and D. Park, “Intrusion Detection System Based on Multi-Class SVM,” RSFDGrC, LNAI, vol. 3642, pp. 511-519, 2005. [LNAI/SCIE]

▣ Domestic Journal (Republic of Korea)

H. Lee and Y. Cho, "Machine Learning-based Power Usage Abnormality Detection", Journal of The Korea Society of Computer and Information vol. 29, no. 11, pp. 107-112, 2024 .
H. Lee, Y. Jeong, S. Jung, "Intrusion Detection Approach using Feature Learning and Hierarchical Classification", J. of KIECS, vol. 19, no. 1, pp. 249-255, 2024.
H. Lee, K. Kim, W. Kim, T. Woo, S. Jung, "X-Ray Security Checkpoint System Using Storage Media Detection Method Based on Deep Learning for Information Security", J. of KMS, vol. 25, no. 10, pp. 1445-1459, 2022.
S. Jung, H. Lee, J. Kim, C. Sim, "A Novel on Auto Imputation and Analysis Prediction Model of Data Missing Scope based on Machine Learning", J. of KMS, vol. 25, no. 2, pp. 257-268, 2022.
H. Park, S. Byun, H. Lee, "Application of Deep Learning Method for Real-Time Traffic Analysis using UAV", J. of KSSGPC, vol. 38, no. 4, pp. 353-361, 2020.
H. Lee, S. Jung, "Analysis Model Evaluation based on IoT Data and Machine Learning Algorithm for Prediction of Acer Mono Sap Liquid Water", J. of KMMS, vol. 23, no. 10, pp. 1286-1295, 2020.
D. Moon, H. Lee, I. Kim,"Host based Feature Description Method for Detecting APT Attack ", Journal of KIISC, vol. 24, no. 5, pp. 839-850 , 2014.
S. Oh, J. Lee, H. Lee, J. Chung, D. Park, “Abnormal Sound Detection and Identification in Surveillance System”, Journal of KIISE: SW & App., vol. 39, no. 2, pp. 114-152, 2012.
H. Kim, S. Lee, J. Chung, D. Park, H. Lee, “Multicore Processor based Parallel SVM for Video Surveillance System”, Journal of KIISC, vol. 21, no. 6, pp. 161-169, 2011.
H. Jung, J. Lee, J. Yu, H. Lee, D. Park, “In-depth Analysis of Soccer Game via Webcast and Text Mining”, J. of KoCon.a, vol. 17, no. 10, pp. 59-68, November 2011.
H. Jung, J. Lee, H. Lee, J. Chung, D. Park, “Face Recognition based Player Identification in Soccer Video”, Journal of KIISE : SW & App., vol. 38, no. 11, pp. 626-632, 2011.
J.Lee,B.Kang,H.Lee,J.Chung,D.Park,“A Suspected Criminal Face Identification via SVDD and SRC in Surveillance System”,J. of KIISE:Comp.Pract.&Lett.,vol.17, no.2, pp.135-139,2011.
H. Lee, Y. Jung, J. Kim, H. Cho, “A Survey of Face Recognition Technologies and Standards”, JKIIT, vol. 8, no. 1, pp. 33-41, 2010.
B. Kang, H. Jung, H. Lee, Y. Im, J. Chung, D. Park, “Real Time Watch List Identification System using a Hybrid Hierarchical SVM”, JSE, vol. 7, no. 5, pp. 479-493, 2010.
H. Lee, Y. Im, J. Yu, S. Oh, D. Park, “A News Video Mining based on Multi-modal Approach and Text Mining”, Journal of KIISE: Database, vol. 37, no. 3, pp. 127-136. 2010.
J. Yu, H. Lee, Y. Im, M. Kim, D. Park, “Internet Application Traffic Classification using a Hierarchical Multi-class SVM”, Journal of Korean Institute of Intelligent Systems, vol. 20, no. 1, pp. 7-14. 2010.
H. Lee, Y. Im, D. Park, S. Lee, “News Video Shot Boundary Detection using Singular Value Decomposition and Incremental Clustering”, Journal of KIISE: SW & App., vol. 36, no. 2, pp. 169-177, 2009.
J. Yu, J. Park, H. Lee, M. Kim, D. Park, “Traffic Flooding Attack Detection on SNMP MIB Using SVM”, KTSDE, vol. 15-C, no. 5, pp. 351-358, 2008.
H. Lee, Y. Im, J. Park, and D. Park, “A New Anchor Shot Detection System for News Video Indexing”, J. of KIIS, vol. 18, no. 1, pp. 133-138, 2008.
D. Moon, S. Jung, T. Kim, H. Lee, J. Chung, J. Yang, E. Choi, C. Seo, “Protecting Fingerprint Data for Remote Applications”, Journal of KIISC, vol. 16, no. 6, pp. 63-71, 2006.
H. Lee, J. Song, E. Kim, C. Lee, D. Park, “Intrusion Detection System Based on Multi-Class SVM”, J. of KIIS, vol. 15, no. 3, pp. 282-288, 2005.
J. Park, J. Kim, H. Lee, D. Park, “One-Class Support Vector Learning and Linear Matrix Inequality”, Int. J. of Fuzzy Logic and Intelligent Systems, vol.3, no.1, pp. 100-104, 2003.
H. Lee, Y. Im, J. Park, D. Park, “Adaptive Intrusion Detection System Based on SVM and Clustering”, Journal of KIIS, vol. 13, no. 2, pp. 237-242, 2003.
H. Lee, J. Park, D. Park, “Hyper-ellipsoidal clustering algorithm using Linear Matrix Inequality”, Journal of KIIS, vol. 12, no. 4, pp. 300-305, 2002.

▣ International Conference

I.Kumari, B. Dung, M. Sharma, E. Jung, H. Lee,"H-Deformable-DETR with Swin Transformer for Enhanced Object Detection in Aerial Imagery," MITA2025, P-4, 2025
S.Jung, J.Park, H.Lee, J.Kim, J.Kim, C.Sim,"A Study on the Data Measurement Scope with Probabilistic Approximation Search in a Data Lack Environment," MITA2021, PA-26, 2021.
S. Jung and H. Lee, "A Study on Data Extraction and Correction for Data Outlier in Data Lack Section," MITA2021, PB-10, 2021.
H. Lee, K. Kim, S. Jung, "Deep learning-based storage media detection for x-ray security checkpoints," MITA2020, pp. 99-102, 2020.
K. Koo, D. Moon, H. Lee, S. Jung, "Attack Graph Learning with Machine Learning ," MITA2020, pp. 97-98, 2020.
H. Lee, A. Grygoriev, Y. Lim, Y. Hong, and J. Kwon, "Generic Object Detection and Localization Combining Saliency and Edge Visual Cues," ISIS2015, pp. 1275-1285, 2015.
A. Grygoriev, H. Lee, J. Kwon, Y. Lim, and Y. Hong, "Fast Generic Object Detection and Localization on The Basis of Superpixel Approach," ISIS2015, pp. 1265-1274, 2015.
J. Kwon, A. Grygoriev, Y. Lim, Y. Hong, and H. Lee, "Edge Fields for Robust Object Proposal," ISIS2015, pp. 1049-1057, 2015.
H. Lee, S. Park, and J. Yoo, “A Data Cube Model for Surveillance Video Indexing and Retrieval,” SIGMAP 2013, pp. 163-168, 2013.
H. Lee, Y. Chung, J. Yoo and C. Won, “Face Recognition Based on Sparse Representation Classifier with Gabor-Edge Components Histogram,” SITIS 2012, 2012.
H. Kim, S. Lee, Y. Chung, D. Park, and H. Lee, “Energy-Efficient Training of SVM on Multicore Platforms,” ATISR 2012, 2012.
J.Yu, H.Lee, B.Lee, M.Kim, and D.Park,“Traffic Flooding Attack Detection and Classification with SNMP MIB via SVDD and Sparse Representation,”ICISCEA, pp.26-34, 2011.
Y. Lee, H. Lee, Y. Chung, “Face Identification with Lazy Learning,” Korea-Japan Joint Workshop on Frontiers of Computer Vision, February 2012.
H. Lee, J. Yu, H. Jung, Y. Im, and D. Park, “A New Data Cube System for the Multi-dimensional Analysis of News Videos,” The First Int. Conf. on Emerging Database, 2009.
H. Lee, Y. Im, D. Park, and S. Lee, “A Fast Method for News Video Parsing with Search Space Reduction,” Korea-Japan Joint Workshop on Pattern Recognition, pp. 79-80, 2008.

▣ Domestic Conference (Republic of Korea)

Kumari et al, "Stage Classification of Advanced Persistent Threats with Hybrid Deep Learning Model", KMMS Spring Conference 2025.
M. Kim et al, "A study on Apple Quality Grading Using Machine Lernining", Korea Computer Education Conference 2024.
J. Bang et al, "Design of DenseNet DETER Model for Monitoring Pets", KMMS Fall Conference 2021.
S. Jung et al, "A Novel on Sensitivity Analysis Algorithm based on Data Significant", KMMS Fall Conference 2021.
J. Kim et al, "Design of LAI Estimation Model using Image Contour and Deep Learning", KMMS Fall Conference 2021.
J. Kim et al, "Predicting of Water Quality Change through Correlation Analysis of Water Quality Data", KMMS Fall Conference 2021.
K. Kim et al, " Digital Twin-based VR HMI Development Method for Moving Object Safety", KMMS Fall Conference 2021.
C. Choi et al, "Design of Intelligent Shooting Game AI using Q-Learning", KIECS Fall Conference 2021.
J. Kim et al, "A Study on the Performance Improvement of Mask R-CNN Model using Transformer", KIECS Fall Conference 2021.
K. Kim et al, "GCC-based Web Compiler Design for Coding Learning Knowledge Tracking Data Collection", KIECS Fall Conference 2021.
J. Kim et al, " Design of Facility Crack Detection Model using Transfer Learning", Annual Conference of KIPS 2021.
S. Park et al, "A Study on Performance Improvement of GVQA Model Using Transformer", Annual Conference of KIPS 2021.
J. Kim et al, "Design of a Quantitative Control Amount Prediction Algorithm for Displaying Control Information in a Farm Map", Smart Media Fall Conference, 2021.
J. Park et al, "Autoencoder model design for image data processing", Smart Media Fall Conference, 2021.
H. Lee, "A Short Studt on the Intelligent Intrusion Detection and Classification Method", KMMS Spring Conference, 2021.
H. Lee, D. Moon, M. Han, I. Kim, J. Kim, "Unsupervised Classification of Malware based on Behavior Analysis", KIISC Regional Conference at Chungnam, September 2014.
D. Moon, H. Lee, I. Kim, "Feature Extraction for Host based Anomaly Detection", Korea IEIE Spring Conference, pp. 591-594, June 2014.
H.Lee, H.Jung, D.Moon, J.Yoo, “Human Detection using Sparse Recognition Classifier with Histogram of Oriented Gradient”, KIISE Fall Conf., vol.39, no.2B, pp.222-224, 2012.
H. Lee, Y. Lee, D. Moon, J. Yoo, J. Kim, “Face detection at a distance method based on fixed-PTZ camera control”, IPIU, February 2012.
H.Jung, J.Lee, H.Lee, D.Park, “A Face Recognition Based Player Identification via ULBP and SRC in Soccer Videos”,KIISE Korea Comp. Cong.,vol.8, no.1(A),pp. 446-449, 2011.
H. Jung, J. Lee, H. Lee, D. Park, “A Multi-dimensional Analysis of Soccer Video using Data Cube”, KIISE Korea Computer Congress, vol. 38, no. 1(C), pp. 21-24, 2011.
Y. Jung, H. Lee, S. Park, Y. Lee, “A large-capacity face search system for building a high-tech security environment”, Korea IEIE Spring Conference, pp. 780-782, 2011.
H. Lee, Y. Lee, S. Park, Y. Jung, J. Kim, “Extraction of facial features robust to lighting changes using edge components”, Korea IEIE Spring Conference, pp. 695-697, 2011.
J. Lee, S. Park, H. Lee, D. Park, “A Face Recognition Based Retrieval for Surveillance System”, KIPS Fall Conference, vol. 17, no. 2, pp. 588-591, 2010.
J. Lee, B..Kang, H. Lee, D. Park, “Face recognition-based criminal suspect detection and identification system”, KIISE Fall Conference, vol. 37, no. 2, pp. 127-128, 2010.
J. Yu, J. Park, H. Lee, Y. Im, M. Kim, D. Park, “Network Traffic Analysis on Multi-dimensional Data Cube”, KIISE Fall Conference, vol. 37, no. 2, pp. 100-105, 2010.
S. Oh, Y. Im, H. Lee, D. Park, “Ontology-based video event analysis for KFD web database system”, KIISE Academic Symposium, vol. 3, no. 2, pp. 219-224, 2009.
H.Jung, H. Lee, S. Park, B. Kang, D. Park, “Player Recognition in Soccer Video Using Hybrid Hierarchical SVM”, KIISE Academic Symposium, vol. 3, no. 2, pp. 213-218, 2009.
H. Lee, Y. Im, J. Yu, S. Oh, D. Park, “News video mining using hierarchical clustering technique”, KIISE Academic Symposium, vol. 3, no. 2, pp. 207-212, 2009.
J. Yu, H. Lee, Y. Im, D. Park, “Network traffic analysis system using data mining technique”, KIISE Academic Symposium, vol. 3, no. 2, pp. 185-190, 2009.
J. Yu, Y. Im, H. Lee, D. Park, J. Jang, “A Prediction Model for the Life Satisfaction of Neo-Elderly using SVM”, KIISE Korea Comp. Cong., vol. 36, no. 1, pp. 352-356, 2009.
S. Oh, H. Lee, Y. Im, D. Park, J. Jang, “Hierarchical Analysis of Domestic Gerontological Studies Using Text Mining”, Joint conference of the Korean Family Resources Association, the Korean Mongolian Society, and the Korean Family Resources Management Association, 2009.
Y. Im, J. Yu, H. Lee, D. Park, J. Jang, “Life Satisfaction Prediction Model of Older People Using Decision Tree Technique”, Joint conference of the Korean Family Resources Association, the Korean Mongolian Society, and the Korean Family Resources Management Association, 2009.
M. Jung, J. Yu, H. Lee, Y. Im, D. Park, J. Jang, “Object-based image search for family art therapy database system”, Joint conference of the Korean Family Resources Association, the Korean Mongolian Society, and the Korean Family Resources Management Association, 2009.
J. Yu, S. Oh, H. Lee, J. Park, M. Kim, D. Park, “Semantic Analysis on Traffic Flooding Attacks Detection System”, KIPS Fall Conference, vol. 15, no. 2, pp. 1496-1499, 2008.
J.Yu,B.Kang,H.Lee,J.Park,M.Kim,D.Park,“An In-depth Analysis on Traffic Flooding Attack Detection using Association Rule Mining”,KIPSConf., vol.15, no.2,pp.1563-1566,2008.
J. Yu, J. Park, H. Lee, M. Kim, D. Park, “Detection of Traffic Flooding Attacks using SVDD and SNMP MIB”, KIISE Korea Comp. Cong., vol. A, vo. 35, no. 1, pp. 124-127, 2008.
J.Yu, S.Kim, H.Lee, M.Kim, D.Park, “Internet Application Traffic Classification using a Hierarchical Multi-class SVM”, KIISE Korea Comp. Cong.,vol.A35,no.1,pp.174-178, 2008.
H. Lee, Y. Im, J. Park, and D. Park, “A New Anchor Shot Detection System for News Video Indexing”, KFIS Fall Conference, vol. 17, no. 2, pp. 217-220, 2007. (Excellent Paper)
J. Yu, H. Lee, Y. Chung, S. Choi, S. Yang, D. Park, “Lightweight Intrusion Detection for Ubiquitous Home Networks”, KIISC Summer Conference, vol. 16, pp. 269-272, 2006.
J. Song, H. Lee, Y. Im, D. Park, “Real-time Face Detection System using Cascade structure and SVDD”, KIISE Korea Computer Congress, vol. B, pp. 763-765, 2005.
H. Lee, Y. Im, J. Park, and D. Park, “Intrusion detection algorithm based on clustering”, KIFS Spring Conference, vol. 12, no. 1, pp. 109-113, 2002.
H. Lee, J. Park, D. Park, “Hyper-ellipsoidal clustering algorithm using Linear Matrix Inequality”, KIFS Spring Conference, vol. 12, no. 1, pp. 215-218, 2002. (Excellent Paper)

▣ Book

H. Lee et al., Data and Coding, ISBN(979-11-94516-01-9), 2024.
H. Lee et al., Python Basic Test, ISBN(979-11-94516-02-6), 2024.
H. Lee et al., Power Point Practice for Media Usage, ISBN(979-11-94516-03-3), 2024.
H. Lee et al., C Language Step, ISBN(979-11-92719-22-1), 2022.11.
S. Jung, H. Lee, C. Sim, J. Kim, J. Park, Python Start, ISBN(979-11-92065-03-8), 2021.11.

Last Updated : 17 June, 2025.

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