• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.455-464
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• 2020

With a variety of data types and high utilization of data, non-relational databases are a popular data storage because it supports better availability and scalability. The increasing use of this technology also brings the risk of NoSQL injection attacks. Existing works mostly discuss the rule-based detection of NoSQL injection attacks that it is hard to deal with NoSQL queries beyond the coverage of the rules. In this paper, we propose a model for detecting NoSQL injection attacks. Our model is based on deep learning algorithms that select features from NoSQL queries using CNN, and classify NoSQL queries using RNN. Also, we experiment the proposed model to compare with existing models, and find that our model outperforms traditional models in terms of detection rate.

• Journal of Internet Computing and Services
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• v.5 no.2
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• pp.97-105
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• 2004

The reason that an intelligent agent cannot understand the representation of its own perception or activity is caused by the traditional syntactic approach that translates a semantic feature into a simulated string, To implement an autonomously learning intelligent agent, Cohen introduces a experimentally semantic approach that the system learns a contentful representation of physical schema from physically interacting with environment using its own sensors and effectors. We propose that negation is a meta-level schema that enables an agent to recognize its own physical schema, To improve the planner's efficiency, Graphplan introduces the control rule that manipulates the inconsistency between planning operators, but it cannot cognitively understand negation and suffers from redundancy problem. By introducing a negative function not, IPP solves the problem, but its approach is still syntactic and is inefficient in terms of time and space. In this paper, we propose that, to represent a negative fact, a positive atom, which is called opposite concept, is a very efficient technique for implementing an cognitive agent, and demonstrate some empirical results supporting the hypothesis.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• Journal of the Korea Fashion and Costume Design Association
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• v.20 no.4
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• pp.105-115
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• 2018

This paper presents an investigation into Cheollik based on 288 records about it at the homepage of The Annals of the Joseon Dynasty on the Internet. Cheollik was called in diverse names and worn by various social classes from kings to common people, but it was solidified as clothes for military officers toward the latter half of Joseon. Not only did it serve the purpose of clothes, but it also was used for a royal grant, diplomacy, shrouding a corpse, and royal coffin. It served the diplomatic purposes a lot especially during the reign of King Sejo and King Seongjong. Cheollik was usually made of cotton, hemp, silk, and mixed fabric with silk used most. Its major colors include white, green, red, blue, black, purple, grey, and yellow with white used most. The fabrics and colors of Cheollik became simplified toward the latter half of Joseon. Silk was most used in Cheollik for a royal grant, shrouding a corpse, and royal coffin. White was most used in Cheollik for kings' visit to royal tombs or their participation in ancestral rites. There were limitations with the selection of materials according to the social status and situations. It was stipulated that only Sa and Ju were used to make Cheollik for Dangsangguan and Danghaguan. Cheollik made of silk was banned for country residents and merchants. The color of Cheollik for Danghaguan was changed to blue and then red. Of military officers, only those who had a Gonsu title or higher were allowed to wear Cheollik made of silk in various colors. In the end, Cheollik was abolished for its low convenience and efficiency during the rule of King Gojong.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.95-104
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• 2019

Recently, software education has been emphasized as a key element of the fourth industrial revolution. Many universities are strengthening the software education for all students according to the needs of the times. The use of online content is an effective way to introduce SW education for all students. However, the provision of uniform online contents has limitations in that it does not consider individual characteristics(major, sw interest, comprehension, interests, etc.) of students. In this study, we propose a recommendation method that utilizes the directional similarity between contents in the boolean view history data environment. We propose a new item-based recommendation formula that uses the confidence value of association rule analysis as the similarity level and apply it to the data of domestic paid contents site. Experimental results show that the recommendation accuracy is improved than when using the traditional collaborative recommendation using cosine or jaccard for similarity measurements.

• Herbal Formula Science
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• v.27 no.1
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• pp.31-44
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• 2019

Objective : Herbal dispensaries, where medications are prepared for patients, require specific preparation and operations management for safe herbal medicines. This study aims to propose improvements in the herbal medicine preparation and operation of the herbal dispensaries as series study of the "A Survey on the Management Status of Extramural Herbal Dispensaries" Methods : We first checked current management regulations. In addition, we compared and analyzed related laws which are "State management norm of Traditional Chinese Medicine dispensaries", "Enforcement Rule of Medicinal Product Safety" and " Hazard Analysis and Critical Control Point(HACCP)", to introduce the assessment items of herbal dispenses evaluation and certification system. Results : In this study, we found that the current regulations, "Guideline on Installation and Utilization of Extremal Herbal Pharmaceutical Facility and Shared-use of Herbal Dispensary", are insufficient to ensure the quality and safety of herbal medicines. We suggested articles for the proper management of herbal dispensaries and these were introduced to the Herbal dispensary evaluation and certification system. Conclusion : We recommend evaluation articles in Herbal dispensary evaluation and certification systems need to be popular among herbal dispensaries, then Korean herbal medicine could restore credibility from the people.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• Korea Trade Review
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• v.41 no.2
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• pp.123-157
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• 2016

As the WTO·DDA continues to stagnate, mega FTAs such as the TPP will likely play the leading role in rule-making of trade for some time to come, creating a 'spaghetti bowl' of trade rules. FTAs, notably high-standard and broad-based regional or mega-FTAs, are the appropriate means to achieve this objective, because they cover many of the policy measures that are needed for the development of global value chains(GVC). The highest quality FTAs are increasingly adding new features like regulatory harmonization that may also foster GVC growth in partner countries. Complementary relationships among markets along value chains, involving both goods and services, also complicate analysis. This is particularly relevant when thinking about policy, since the traditional tendency to think about policies and regulate markets in unconnected silos can lead to unintended and undesirable results. This paper examines the current states of FTAs to determine which are more likely to push this latest wave of globalization further and faster, and explores the plans that are most helpful for GVC growth.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.16-24
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• 2007

Voice activity detectors (VADs) are important in wireless communication and speech signal processing. In the conventional VAD methods. an expression for the likelihood ratio test (LRT) based on statistical models is derived. Then, speech or noise is decided by comparing the value of the expression with a threshold. We propose a new method with the modified decision rule based on the Gaussian distribution and the uniformly most power (UMP) test. This method requires the distribution of the absolute value of the incoming speech signal. Then we can obtain the final decision through the relation between the Rayleigh distributions. This VAD method can detect speech without a priori signal-to-noise ratio (SNR) which is required in the conventional VAD algorithms. Additionally, in the various VAD performance tests, the proposed VAD method is shown to be more effective than the traditional scheme.

• Geomechanics and Engineering
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• v.38 no.3
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• pp.215-229
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• 2024

Because of the various patterns of deep-water inrush and complicated mechanisms, accurately predicting mine water inflows is always a difficult problem for coal mine geologists. In study presented in this paper, the water inrush channels were divided into four basic water diversion structures: aquifer, rock fracture zone, fracture zone and goaf. The fluid flow characteristics in each water-conducting structure were investigated by laboratory tests, and multistructure and multisystem coupling flow analysis models of different water-conducting structures were established to describe the entire water inrush process. Based on the research of the water inrush flow paths, the analysis model of different water inrush space structures was established and applied to the prediction of mine water inrush inflow. The results prove that the conduction sequence of different water-conducting structures and the changing rule of permeability caused by stress changes before and after the peak have important influences on the characteristics of mine water-gushing. Influenced by the differences in geological structure and combined with rock mass RQD and fault conductivity characteristics and other mine exploration data, the prediction of mine water inflow can be realized accurately. Taking the water transmitting path in the multistructure as the research object of water inrush, breaking through the limitation of traditional stratigraphic structure division, the prediction of water inflow and the estimation of potentially flooded area was realized, and water bursting intensity was predicted. It is of great significance in making reasonable emergency plans.