• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.2
• /
• pp.632-657
• /
• 2022

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed WAF model. The classification process of the types of abnormal traffics is postponed to the second stage and carried out using an integrated stacked ensemble model. By this way, clients' requests can be served without time delay, and attack types can be detected with high sensitivity. In addition to the high accuracy of the proposed model, by using the statistical similarity and diversity analyses in the study, high generalization for the ensemble model is achieved. Within the study, a comprehensive, up-to-date, and robust multi-class web anomaly dataset named GAZI-HTTP is created in accordance with the real-world situations. The performance of the proposed WAF model is compared to state-of-the-art deep learning models and previous studies using the benchmark dataset. The proposed two-stage model achieved multi-class detection rates of 97.43% and 94.77% for GAZI-HTTP and ECML-PKDD, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.5
• /
• pp.1186-1207
• /
• 2024

Bearings are one of the main components of mechanical equipment and one of the primary components prone to faults. Therefore, conducting fault diagnosis on bearings is a key issue in mechanical equipment research. Belief rule base (BRB) is essentially an expert system that effectively integrates qualitative and quantitative information, demonstrating excellent performance in fault diagnosis. However, class imbalance often occurs in the diagnosis task, which poses challenges to the diagnosis. Models with interpretability can enhance decision-makers' trust in the output results. However, the randomness in the optimization process can undermine interpretability, thereby reducing the level of trustworthiness in the results. Therefore, a hierarchical BRB model based on extreme gradient boosting (XGBoost) feature selection with interpretability (HFS-IBRB) is proposed in this paper. Utilizing a main BRB alongside multiple sub-BRBs allows for the conversion of a multi-classification challenge into several distinct binary classification tasks, thereby leading to enhanced accuracy. By incorporating interpretability constraints into the model, interpretability is effectively ensured. Finally, the case study of the actual dataset of bearing fault diagnosis demonstrates the ability of the HFS-IBRB model to perform accurate and interpretable diagnosis.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.11S
• /
• pp.3243-3250
• /
• 1999

There are many problems to be satisfied the various commercial demand in the present VRML node, and the VRML-based system by the contact with other technology is burdened with the direct participation of developer related with it. In this study, remote control and monitoring system using EAI(External Authoring Interface) is reposed to overcome the limit of VRML. In other words, This study is about mechanism of interaction between control and monitoring subject in real world and object in virtual world mapped with it. Object oriented method by one to one mapping of the Java class which have VRML virtual world and the object control is proposed. Introduction method of video monitoring through method of image synthesis and the integrated development environment is described. Finally automobile-gate control system based on the development method of Internet virtual reality-based system which is proposed in this study is described.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.149-159
• /
• 2023

Web application security education that can provide practical experience is needed to reduce damage caused by the recent increase in web application vulnerabilities and to strengthen security. In this paper, we proposed a scenario-based web application education method, applied the proposed method to classes, and analyzed the results. In order to increase the effectiveness of scenario-based education, a real-life practice environment to perform scenarios and instructions to be performed by learners are needed. As an example of the proposed method, instructions to be performed by learners from the viewpoint of the attacker and the victim were shown in a practice environment to teach XSS and SQL injection vulnerabilities. After applying the proposed method to the class for students majoring in cyber security, when the lecture evaluation results were analyzed, it was shown that the learner's interest, understanding, and major ability all improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.1
• /
• pp.83-88
• /
• 2024

In this research, we propose a Semi-Supervised learning based railroad surface defect detection method. The Resnet50 model, pretrained on ImageNet, was employed for the training. Data without labels are randomly selected, and then labeled to train the ResNet50 model. The trained model is used to predict the results of the remaining unlabeled training data. The predicted values exceeding a certain threshold are selected, sorted in descending order, and added to the training data. Pseudo-labeling is performed based on the class with the highest probability during this process. An experiment was conducted to assess the overall class classification performance based on the initial number of labeled data. The results showed an accuracy of 98% at best with less than 10% labeled training data compared to the overall training data.

• Journal of the Korean Society for information Management
• /
• v.30 no.3
• /
• pp.49-70
• /
• 2013

The purposes of this study are to analyze and compare current state of subject directories of the health field in eight internet bookstores in domestic and abroad. A comparative analysis was carried out for KDC and DDC, using names of subdivisions within the health field of internet bookstore. Also, user interviews to find their information needs about the health field in internet bookstore were conducted. And then, based upon the findings, this study proposed a design principle and a new classification for the health field of internet bookstores. With evaluations of the experts from the field, a final classification schedule (1 class, 11 division, 60 subdivision, and 16 section) was suggested. The results of this study can be used for a foundation of classifying health resources efficiently in internet bookstores and other web sites.

• Journal of Information Processing Systems
• /
• v.20 no.3
• /
• pp.307-316
• /
• 2024

In the realm of large-scale identification deployments, the EPCglobal Class-1 Generation-2 (Gen2) standard serves as a cornerstone, facilitating rapid processing of numerous passive RFID tags. The Q-Algorithm has garnered considerable attention for its potential to markedly enhance the efficiency of Gen2-based RFID systems with minimal adjustments. This paper introduces a groundbreaking iteration of the Q-Algorithm, termed Time-Efficient Q-Algorithm (SwiftQ), specifically designed to push the boundaries of time efficiency within Gen2-based RFID systems. Through exhaustive simulations, our study substantiates that SwiftQ outperforms existing algorithms by a significant margin, demonstrating exceptional expediency that positions it as a formidable contender in the landscape of large-scale identification environments. By prioritizing time efficiency, SwiftQ offers a promising solution to meet the escalating demands of contemporary Internet of Things applications, underscoring its potential to catalyze advancements in RFID technology for diverse industrial and logistical contexts.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.4
• /
• pp.55-62
• /
• 2016

In this paper, we propose the INDEM(Internet News Data Extraction Middleware) system for the removal of the unnecessary data in internet news. Although data on the internet can be used in various fields such as source of data of IR(Information Retrieval), Data mining and knowledge information service, it contains a lot of unnecessary information. The removal of the unnecessary data is a problem to be solved prior to the study of the knowledge-based information service that is based on the data of the web page. The INDEM system parses html and explores the XPath, and it is to perform the analysis. The user simply utilize INDEM by implementing an abstract class that provides INDEM, and can obtain the analysis information. INDEM System through this process delivers the analysis information including the main contents of news site to the users. In this paper, the INDEM system was adapted in a stand-alone and web service system and it was evaluated on the basis of 16 news site. As a result, performance of the INDEM system is affected in html source data size and complexity of used html grammar than the main news data size.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.711-712
• /
• 2008

We developed a XMAS (X Multimedia Analysis System) for analyzing the illegal and objectionable multimedia in Internet environment based on Web2.0. XMAS uses the MPEG-7 visual descriptor and multi-class SVM (support vector machine) and its performance (accuracy on precision) is about 91.6% for objectionable multimedia analysis and 99.9% for illegal movie retrieval.

• Journal of Fisheries and Marine Sciences Education
• /
• v.21 no.4
• /
• pp.499-507
• /
• 2009

The purpose of this study was to improve teachers' instruction and to identify the characteristics of interaction between teachers and children. Field excellent class instructions, which were known as the best lectures from the competition of an instruction contest in Busan, were video recorded and openly released on the internet. A teacher who won a prize for his excellent teaching at the contest demonstrated a Korean subject class on sixth grade elementary school curriculum. His instruction was analyzed by two coders based on the frame of Flanders' language interaction system. Inter-coder reliability was .967 from Scott's coefficient. From the results of the Flanders index, the major and minor instruction sequences were 4-8-2-5 and 6-0-5-4, and the teacher tended to interact with students by accepting feeling and ideas. These results could provide effective cues and information on how to to improve instruction.