• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.5
• /
• pp.1087-1097
• /
• 2017

As the penetration rate of smartphones increases, the number of malicious codes targeting smartphones is increasing. I 360 Security 's smartphone malware statistics show that malicious code increased 437 percent in the first quarter of 2016 compared to the fourth quarter of 2015. In particular, malicious applications, which are the main means of distributing malicious code on smartphones, are aimed at leakage of user information, data destruction, and money withdrawal. Often, it is operated by an API, which is an interface that allows you to control the functions provided by the operating system or programming language. In this paper, we propose a mechanism to detect malicious application based on the similarity of API pattern in normal application and malicious application by learning pattern of API in application derived from static analysis. In addition, we show a technique for improving the detection rate and detection rate for each label derived by using the corresponding mechanism for the sample data. In particular, in the case of the proposed mechanism, it is possible to detect when the API pattern of the new malicious application is similar to the previously learned patterns at a certain level. Future researches of various features of the application and applying them to this mechanism are expected to be able to detect new malicious applications of anti-malware system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.2
• /
• pp.76-86
• /
• 2016

SQL Injection attacks are the most widely used and also they are considered one of the oldest traditional hacking techniques. SQL Injection attacks are getting quite complicated and they perform a high portion among web hacking. The big data environments in the future will be widely used resulting in many devices and sensors will be connected to the internet and the amount of data that flows among devices will be highly increased. The scale of damage caused by SQL Injection attacks would be even greater in the future. Besides, creating security solutions against SQL Injection attacks are high costs and time-consuming. In order to prevent SQL Injection attacks, we have to operate quickly and accurately according to this data analysis techniques. We utilized data analytics and machine learning techniques to defend against SQL Injection attacks and analyzed the execution plan of the SQL command input if there are abnormal patterns through checking the web log files. Herein, we propose a way to distinguish between normal and abnormal SQL commands. We have analyzed the value entered by the user in real time using the automated SQL Injection attacks tools. We have proved that it is possible to ensure an effective defense through analyzing the execution plan of the SQL command.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.11-20
• /
• 2021

This study extracts topics related to university education through newspaper articles and analyzes the characteristics of each topic and the reporting patterns of each newspaper. The 9 topics were discovered using LDA. Topic 1 and Topic 3 are related to university support projects for education, but Topic 3 is focused on local universities. Topic 2 is about university education after COVID-19, Topic 4 teaching-learning methods, Topic 5 government policies, Topic 6 the high school education contribution university support projects, Topic 7 the university education vision, Topic 8 internationalization, and Topic 9 the entrance exam. The Chosun Ilbo, Kyunghyang, and Hankyoreh reported a lot of articles associated to lectures after COVID-19, government policies, and comments on university education. Relevant articles since 2016 have been analyzed by newspaper type and before/after COVID-19 through which differences in the topics were studied and discussed. These findings would suggest a basic policy guideline for university education and imply that the positive and negative effects of the media need to be considered.

• The Journal of the Korea Contents Association
• /
• v.19 no.8
• /
• pp.23-34
• /
• 2019

The space before modern times is fixed and closed, then that after modern times is flexible and open. Based on the concept of space, the modern art exhibition hall gradually shifts from the interior space of a building to the outdoor space, giving birth to the concept of outdoor art pavilion. Based on this background, we analyzed and learned about the latest deformable art pavilions, focused on the investigation of its space performance characteristics and the case analysis, fully understood the design principles of deformable pavilions, and proposed the basic design directions and strategies for future research. Firstly, through learning the theories of transformable space, the characteristics and concept range of deformable space are understood. Secondly, based on the preliminary research and analysis of art pavilions, the performance characteristics are summarized. Thirdly, the pattern of deformable space and the method of reflecting the characteristics of deformable space are investigated based on cases. After summarizing the case analysis, we identified the differences of different art pavilions between deformable modes and space characteristics, and analyzed the causes. This work provides a basis for distinguishing the transformation patterns of the deformable space, and reveals the changes in space concepts and the expansion of space meaning in future architectural space design.

• 재활복지
• /
• v.20 no.4
• /
• pp.79-106
• /
• 2016

This study examined the meanings of the disability education of the mothers who reared their children with brain lesions. For this purpose, Rennie's hermeneutic grounded theory was applied and the consented 7 mothers participated in this study. With the in-depth interviews, 53 meaning units, 16 subordinate categories and 7 hermeneutic categories were classified. These 7 hermeneutic categories were 'wailing miserably everyday', 'social mobilization of the surroundings', 'straight forward', 'smash rock with the eggs', 'looking at a faraway', 'learning together' and 'subjectivation of disability education.' The experience of disabled children education process was concurrent experience of frustration and hoping that moving toward a big hope through the resignation stage, the chasing stage, the vision stage, the challenge stage, and the small achievement stage. Repetitive common patterns of behavior revealed three types: wishy-washy type, realistic-strategy type, and indomitable-challenge type. Moreover, the core category of educational experience was concluded to be 'a pedagogical process of turning despair from severe disabilities into hope through education.' Based on the analysis results, concrete intervention plans for social welfare practice were suggested to support the disabled children's lives with high quality of education.

• Phonetics and Speech Sciences
• /
• v.13 no.4
• /
• pp.9-21
• /
• 2021

This study investigated whether Korean learners improve acoustic cue weights to identify Korean lenis and aspirated stops in the direction of native values through perception training that focused on contrasting the stops in various phonetic contexts. Nineteen native Chinese learners of Korean and two native Korean instructors for the perception training participated in the experiment. A training group and a non-training group were divided according to pretest results, and only the training group participated in the training for 5 days. To estimate the perceptual weights of the stop cues, a pretest and a posttest were conducted with stimuli whose stop cues (F0 and VOT) were systematically manipulated. Binary logistic regression analyses were performed on each learner's test results to calculate perceptual β coefficients, which estimate the perceptual weights of the acoustic cues used in identifying the stop contrast. The training group showed a statistically significant increase of 0.451 on average in the posttest for the coefficient values of the F0, which is the primary cue for the stop contrast, whereas the non-training group showed an insignificant increase of 0.246. The patterns of change in the F0 use after training varied considerably among individual learners.

• Journal of Korean Society of Archives and Records Management
• /
• v.21 no.4
• /
• pp.1-18
• /
• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.49 no.4
• /
• pp.357-367
• /
• 2022

Sleep disordered breathing (SDB) is a disease characterized by repeated hypopnea and apnea during sleep due to complete or partial obstruction of upper airway. The prevalence of pediatric SDB is approximately 12 - 15%, and the most common age group is preschool children aged 3 - 5 years. Children show more varied presentations, from snoring and frequent arousals to enuresis and hyperactivity. The main cause of pediatric SDB is obstruction of the upper airway related to enlarged tonsils and adenoids. If SDB is left untreated, it can cause complications such as learning difficulties, cognitive impairment, behavioral problems, cardiovascular disease, metabolic syndrome, and poor growth. Pediatric dentists are in a special position to identify children at risk for SDB. Pediatric dentists recognize clinical features related to SDB, and they should screen for SDB by using the pediatric sleep questionnaire (PSQ), lateral cephalometry radiograph, and portable sleep monitoring test and refer to sleep specialists. As a therapeutic approach, maxillary arch expansion treatment, mandible advancement device, and lingual frenectomy can be performed. Pediatric dentists should recognize that prolonged mouth breathing, lower tongue posture, and ankyloglossia can cause abnormal facial skeletal growth patterns and sleep problems. Pediatric dentists should be able to prevent these problems through early intervention.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.11
• /
• pp.449-456
• /
• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of the Korea Computer Graphics Society
• /
• v.28 no.2
• /
• pp.1-9
• /
• 2022

In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.