• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.225-234
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• 2015

With the growing number of people that use web services, the perception of the importance of securing web applications is also increasing. There are many different types of attacks that target web applications. In the rapidly-changing knowledge and information society, which came into being with the advancements made in information and communication technology, there is currently an urgent need for building web sites for the purposes of developing one's creativity and character. In this paper, attack schemes that use SQL injections and XSS and target educational digital curation systems which provide educational contents with the aim of developing of one's creativity and character are analyze, in terms of how the attacks are carried out and their vulnerabilities. Furthermore, it suggests ways of dealing appropriately with these web-based attacks that use SQL injections and XSS.

• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.659-667
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• 2005

A Mobile Ad Hoc Network(MANET) is a multi hop wireless network with no prepared base stations or centralized administrations, where flocks of peer systems gather and compose a network. Each node operates as a normal end system in public networks. In addition to it, a MANET node is required to work as a router to forward traffic from a source or intermediate node to others. Each node operates as a normal end system in public networks, and further a MANET node work as a router to forward traffic from a source or intermediate node to the next node via routing path. Applications of MANET are extensively wide, such as battle field or any unwired place; however, these are exposed to critical problems related to network management, node's capability, and security because of frequent and dynamic changes in network topology, absence of centralized controls, restricted usage on network resources, and vulnerability oi mobile nodes which results from the special MANET's character, shared wireless media. These problems induce MANET to be weak from security attacks from eavesdropping to DoS. To guarantee secure authentication is the main part of security service In MANET because networks without secure authentication are exposed to exterior attacks. In this paper, a multistage authentication strategy based on CGSR is proposed to guarantee that only genuine and veritable nodes participate in communications. The proposed authentication model is composed of key manager, cluster head and common nodes. The cluster head is elected from secure nodes, and key manager is elected from cluster heads. The cluster head will verify other common nodes within its cluster range in MANET. Especially, ID of each node is used on communication, which allows digital signature and blocks non repudiation. For performance evaluation, attacks against node authentication are analyzed. Based on security parameters, strategies to resolve these attacks are drawn up.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.667-667
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• 2004

We must design the buffer algorithm that protects traffic congestion and decreasing throughput at satellite communication network. It is important that buffer algorithm is satisfied with the good performance of transmission packet, responsibility of many connecting traffic and the QOS for connecting character. Old buffer algorithms are not the suitable algorithms when we have the satellite communication network environment. RED buffer algorithm is proposed by Floyd. It has a better performance than old buffer algorithm. But this algorithm is not well adapted a number of connecting TCP packet and changing network, so this algorithm has a bad performance on satellite communication network that is many of connecting user at same time. This paper propose the TARED(Target Adaptive RED). It has a good performance, adaptation and stability on satellite communication network and has not overflow and underflow of the buffer level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.666-676
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• 2004

We must design the buffer algorithm that protects traffic congestion and decreasing throughput at satellite communication network. It is important that buffer algorithm is satisfied with the good performance of transmission packet, responsibility of many connecting traffic and the 005 for connecting character. Old buffer algorithms are not the suitable algorithms when we have the satellite communication network environment. RED buffer algorithm is proposed by Floyd. It has a better performance than old buffer algorithm. But this algorithm is not well adapted a number of connecting TCP packet and changing network, so this algorithm has a bad Performance on satellite communication network that is many of connecting user at same time. This paper Propose the TARED(Target Adaptive RED). It has a good performance, adaptation and stability on satellite communication network and has not overflow and underflow of the buffer level.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.24 no.4
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• pp.191-198
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• 2013

Objectives : The objective of this study is to find out the differences in psychopathology, temperament, and character factors between young adults with and without childhood attention-deficit hyperactivity disorder (ADHD) symptoms. Methods : The subjects consisted of 314 university students (male=72, female=242) in Gongju. They were divided into childhood ADHD group (N=54) and normal group (N=260) to the Wender-Utah Rating Scale. Participants were assessed using Korean Adult ADHD Scale, Beck Depression Inventory-II, Beck Anxiety Inventory, Kimberly Young's Internet Addiction Test, Barratt Impulsiveness Scale, Paranoia Scale, Korean-Schizotypal Ambivalence Scale, Lubben Social Network Scale, and Temperament and Character Inventory-Revised. Descriptive statistics, t-test, chi-square, spearman correlation, and stepwise multiple regression were applied to analyze the data. Results : Participants with childhood ADHD symptoms had high level of adult ADHD symptoms (p<.001), impulsiveness (p=.001), depression (p<.001), anxiety (p<.001), internet addiction (p<.001), paranoia tendency (p<.001) and low level of selfesteem (p<.001) compared to normal group. Self-directedness (p<.001) was lower, Harm avoidance (p=.001) and Self-transcendence (p=.029) were higher in the childhood ADHD group. In correlation and stepwise multiple regression, childhood ADHD symptoms were significantly associated with cooperativeness (r=-0.515 and ${\beta}$=-0.547, p<.001 respectively). Conclusion : This result showed that young adults with childhood ADHD symptoms had various forms of psychopathology and childhood ADHD symptoms were influenced by character such as cooperativeness. Therefore, more thorough evaluation regarding childhood ADHD symptoms is needed.

• Smart Media Journal
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• v.10 no.2
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• pp.30-37
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• 2021

Recently, 3D contents used in various fields have been attracting people's attention due to the development of virtual reality and augmented reality technology. In order to produce 3D contents, it is necessary to model the objects as vertices. However, high-quality modeling is time-consuming and costly. In order to convert a 2D character into a 3D model, it is necessary to express it as line drawings through feature line extraction. The extraction of consistent line drawings from 2D cartoon cartoons is difficult because the styles and techniques differ depending on the designer who produces them. Therefore, it is necessary to extract the line drawings that show the geometrical characteristics well in 2D cartoon shapes of various styles. This study proposes a method of automatically extracting line drawings. The 2D Cartoon shading image and line drawings are learned by using adversarial network model, which is artificial intelligence technology and outputs 2D cartoon artwork of various styles. Experimental results show the proposed method in this research can be obtained as a result of the line drawings representing the geometric characteristics when a 2D cartoon painting as input.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.307-316
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• 2016

A user usually gets the same suggesting results as everyone else in most of the multimedia social services, nowadays. To address the challenging problem of personalization in the social network, we propose a method which exploits user's activities, user's moods, and user's friend relationships from the social network to build a decision-making system. Depending on a current state of the user's mood, this system infers the most appropriated video for the user. In the system, the user evaluates a set of the given recommendation methods which extract from the user's database social network and assigns a vague value to each method by a weight. Then, we find the fuzzy collection solution for the system and classify the set of methods into subsets, and order the subsets based on its local dominance to choose the best appropriate method. Finally, we conduct an experiment using the YouTube API with a lot of video types. The experiment result shows that the channel recommendation system appropriately affords the user's character, it is more satisfying than the current YouTube based on an evaluation of several users.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.111-114
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• 1997

Usually, Evolutionary Algorithms are considered more efficient for optimal system design, However, the performance of the system is determined by fitness function and system environment. In this paper, in order to overcome the limitation of the performance by this factor, we propose a co-evolutionary method that two populations constantly interact and coevolve. In this paper, we apply coevolution to neural network's evolving. So, one population is composed of the structure of neural networks and other population is composed of training patterns. The structure of neural networks evolve to optimal structure and, at the same time, training patterns coevolve to feature patterns. This method prevent the system from the limitation of the performance by random design of neural network structure and inadequate selection of training patterns. In this time neural networks are trained by evolution strategies that are able to apply to the unsupervised learning. And in the coding of neural networks, we propose the method to maintain nonredundancy and character preservingness that are essential factor of genetic coding. We show the validity and the effectiveness of the proposed scheme by applying it to the visual servoing of RV-M2 robot manipulators.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.270-279
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• 2000

This paper describes the on-chip learning algorithm of neural networks using the stochastic pulse arithmetic. Stochastic pulse arithmetic is the computation using the numbers represented by the probability of 1' and 0's occurrences in a random pulse stream. This stochastic arithmetic has the merits when applied to neural network ; reduction of the area of the implemented hardware and getting a global solution escaping from local minima by virtue of the stochastic characteristics. And in this study, the on-chip learning algorithm is derived from the backpropagation algorithm for effective hardware implementation. We simulate the nonlinear separation problem of the some character patterns to verify the proposed learning algorithm. We also had good results after applying this algorithm to recognize printed and handwritten numbers.