• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.91-98
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• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• Journal of Industrial Convergence
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• v.19 no.1
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• pp.53-63
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• 2021

As tourists travel to other regions, they encounter numerous facts that conflict with their views. At that time, we change our view of coping with life. In this respect, tourism is a new way of learning. As a new learning method, tourism experience research is a new approach. In this study, the relationship between experience and learning experienced in tourist destinations was analyzed by applying the activity theory. The analysis units applied in the activity theory were set as subjects, goals, communities, roles, methods and rules, outcomes, and relevance to local communities. Based on this, in-depth interviews were conducted with commentators and guides who had a great influence on the tourism experience to analyze the learning process of tourists. As a result of the analysis, the experiences of tourists during the tour were interactive in various forms within the unit as well as the unit of the activity system of the commentator and guide. This interaction induces changes in the tourism experience activity system, enabling tourists to learn. The content is that the value of learning increases as the role of guide and commentator increases, that the social and cultural dimension of tourism experience is included in the learning effect, and the contradictions that arise from interactions within or between activity systems. The fact that they find the solution process themselves, and that tourism activity is not an isolated unit, but exists at the intersection of hierarchies and networks, is affected by the activities and environments of others.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.167-176
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• 2021

With development of big data analysis technology, many studies to find social issues using texts mining techniques have been conducted. In order to derive social issues, previous studies performed in a way that collects a large amount of text data from news or SNS, and then analyzes issues based on text mining techniques such as topic modeling and terms network analysis. Social issues are the results of various social phenomena and factors. However, since previous studies focused on deriving social issues that are results of various causes, there are limitations to revealing the cause of the issues. In order to effectively respond to social issues, it is necessary not only to derive social issues, but also to be able to identify the causes of social issues. In this study, in order to overcome these limitations, we proposed a method of deriving the factors that cause social issues from texts related to social issues based on the theory of part of Korean linguistics. To do this, we collected news data related to social issues for three years from 2017 to 2019 and proposed a methodology to find causes based causal sentences based on text mining techniques.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.47-56
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• 2022

The safe driving reward system aims to reduce the loss of life and property by reducing the occurrence of accidents by motivating safe driving and encouraging active participation by providing direct reward to vehicle drivers who have performed safe driving. In the case of the existing digital tachograph, the goal is to limit dangerous driving by recording the driving status of the vehicle whereas the safe driving reward system is a support measure to increase the effect of accident prevention and induces safe driving with financial reward when safe driving is performed. In other words, in an area where accidents due to speeding are high, direct reward is provided to motivate safe driving to prevent traffic accidents when safe driving instructions such as speed compliance, maintaining distance between vehicles, and driving in designated lanes are performed. Since these safe operation data and reward histories must be managed transparently and safely, the reward evidences and histories were constructed using the closed blockchain Hyperledger Fabric. However, while transparency and safety are guaranteed in the blockchain system, low data processing speed is a problem. In this study, the sequential block generation speed was as low as 10 TPS(transaction per second), and as a result of applying the acceleration function a high-performance network of 1,000 TPS or more was implemented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.121-127
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• 2022

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the useer along with the mirror function. This paper went beyond the form of dealing with smart mirrors only stand alone device the provide information to users, and constructed a network in which smart mirrors are connected, and proposed and implemented a CoMirror system that allows users to talk and share information with other smart mirror users. The CoMirror system has a structure in which several CoMirror clients are connected on one CoMirror server. The CoMirror client consists of Raspberry Pi, a mirror film, a touch pad, a display device, an web camera, etc. The server has functions such as face learning and recognition, user management, a relay role for exchanging messages between clients, and setting up for video call. Users can communicate with other CoMirror users via the server, such as text, image, and audio messages, as well as 1:1 video call.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.55-61
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• 2022

Currently police and fire departments use a Network/Wifi/GPS based emergency location positioning system established by mobile carriers to directly link with the device of the people who request the rescue to accurately position the expected location in the call area. However in the case of mountain rescue it is difficult to rescue the victim in golden time because the location of the search area cannot be limited when the victim is located in a radio shadow area of the mountain or the device power is off and this situation become worse if victim fail to report 911 by himself due to the injury. In this paper, we are expected to solve the previous problem by propose the mobile telecommunication forensic simulator consist of time series of cell information, human mobility model which include some general and specific features (age, gender, behavioral characteristics of victim, etc.) and intelligent infer system. The results of analysis appear in heatmap of polygons on the map based on the probability of the expected location information of the victim. With this technology we are expected to contribute to rapid and accurate lifesaving by reducing the search area of rescue team.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.354-360
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• 2021

People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

• Journal of Family Resource Management and Policy Review
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• v.26 no.2
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• pp.53-70
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• 2022

This study aimed to develop a scale to measure the family strength of single-parent families. We analyzed the everyday life and demands of single-parent families using the theory of family strength to draw 78 items that encompass family basis, relationships, roles, social networks and family culture. Using a sample of 286 single-parent families through an online survey platform, we examined the factor structure of the items and selected 48 items based on the results of the factor analysis. Reliability, criterion and construct validity were also examined. The final scale comprised of five domains ; basis, parents' role, work-life balance, social network, lifestyle and household management. This scale can be used as an assessment measure of the family strength of single-parent families for consulting, case management and suggesting various programs in the field. This merit will help enhance the quality of programing for single-parent families at the Healthy Family Support Center and the development of family strength scales for various types of families.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.139-149
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• 2010

Internet was designed for network scalability and best-effort service which makes all hosts connected to Internet to be vulnerable against attack. Many papers have been proposed about attack detection algorithms against the attack using IP spoofing and DoS/DDoS attack. Purpose of DoS/DDoS attack is achieved in short period after the attack begins. Therefore, DoS/DDoS attack should be detected as soon as possible. Attack detection algorithms using false alarm rates consist of the false negative rate and the false positive rate. Moreover, they are important metrics to evaluate the attack detections. In this paper, we analyze the performance of the attack detection algorithms using the impact of false negative rate and false positive rate variation to the normal traffic and the attack traffic by simulations. As the result of this, we find that the number of passed attack packets is in the proportion to the false negative rate and the number of passed normal packets is in the inverse proportion to the false positive rate. We also analyze the limits of attack detection due to the relation between the false negative rate and the false positive rate. Finally, we propose a solution to minimize the limits of attack detection algorithms by defining the network state using the ratio between the number of packets classified as attack packets and the number of packets classified as normal packets. We find the performance of attack detection algorithm is improved by passing the packets classified as attacks.

• The Korean Journal of Coaching Psychology
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• v.5 no.1
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• pp.33-65
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• 2021

This study is an exploratory study to investigate the concept of student success recognized by college students. In order to listen to students' free thoughts, an open questionnaire was conducted using an online questionnaire and 99 responses were analyzed. The response results were analyzed using CQR-M (Consensual Qualitative Research-Modified). As a result of the analysis, 25 categories were derived from three domains. The frist domain, 'meaning of student success' recognized by college students is with 9 categories: 'academic achievement', 'job competency improvement', 'gaining diverse experiences', 'satisfactory employment', 'setting of desired career path', 'relationship-building ability improvement', 'setting and achievement of own goals', 'self-development', and 'satisfactory college life'. The second domain, 'college environmental factors for student success' is with 7 categories: 'career development support', 'job competency improvement system', 'support for participation in college life', 'opportunities to form human networks', 'learning capability enhancement system', 'expansion of economic support', and 'environment for student convenience'. The third domain, 'psychological factors necessary for student success' is with 9 categories: 'learning ability', 'self-efficacy', 'interpersonal competence', 'self-awareness and improvement', 'job competency', 'self-regulation ability', 'rich experience', 'career awareness', and 'self-esteem'. The frequency and results of each domain were analyzed and presented, the significance and limitations of the study were discussed, and suggestions for subsequent studies were made.