• Convergence Security Journal
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• v.13 no.4
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• pp.61-68
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• 2013

Compared to the past, the number of disabled people in Korea is continuing to increase. As for the scope of the disability, it is expanding as well since it now includes all types of illnesses, car accidents, complications resulting from aging, industrial accidents and others accidents. Attempts are made in terms of applying sports game method that grafts IT technology in order to ensure that the disabled people participate continually in sports. While casting away the notion of play which was the role of a game in the past, new roles and domains were developed. In fact, serious game genre is what leads this change. Because serious game is leading the game industry fast, centered on education, sports, fitness and medical use, its market value can be considered very significant since it can be both fund and effective as it targets the disabled who cannot enjoy sports easily in reality. Accordingly, this research seeks to present the direction for the application of serious game for the disabled people by analyzing the current situation pertaining to the integrated and converged cases applied to the field of sports for the disabled when it comes to the serious game that uses contents based on the IT technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.113-124
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• 2009

Recently, lots of anti-phishing schemes have been developed. Several products identify phishing sites and show the results on the address bar of the internet browser, but they determine only by domain names or IP addresses. Although this kind of method is effective against recent DNS pharming attacks, there is still a possibility that hidden attacks which modifies HTML codes could incapacitate those anti-phishing programs. In this paper, the cognitive approach which compares images to decide phishing or pharming is presented, using system tray and balloon tips that are hard to fake with pop-ups or flash in order for users to compare pictures from connecting sites and system tray. It differs from an old method that a program analyzes IP or domains to judge if it is phishing or pharming, but observes if there were HTML code changing between plug-ins and a server.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.71-84
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• 2003

Self-certified public keys need not be accompanied with a separate certificate to be authenticated by other users because the public keys are computed by both the authority and the user. At this point, verifiable self-certified public keys are proposed that can determine which is wrong signatures or public keys if public keys are used in signature scheme and then verification of signatures does not succeed. To verify these public keys, key generation center's public key trusted by users is required. If all users trust same key generation center, public keys can be verified simply. But among users in different domains, rusty relationship between two key generation centers must be accomplished. In this paper we propose inter-domain verifiable self-certified public keys that can be verified without certificate between users under key generation centers whose trusty relationship is accomplished. Also we present the execution of signature and key distribution between users under key generation centers use different public key parameters.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.53-63
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• 2011

An SNS(Social Network Service) enables people to form a social network on online as in the real world. With the rising popularity of the service, side effects of SNSs were issued. Therefore we propose and implement a policy-based privacy protection module and access control policy language for ensuring the right of control of personal information and sharing data among SNSs. The policy language for protecting privacy is based on an attribute-based access control model which grants an access to personal information based on a user's attributes. The policy language and the privacy protection module proposed to give the right of control of personal information to the owner, they can be adopted to other application domains in which privacy protection is needed as well as secure sharing data among SNSs.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.57-66
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• 2023

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.

• Convergence Security Journal
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• v.22 no.5
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• pp.145-154
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• 2022

Recently, the widespread proliferation and high sophistication of botnets are having serious consequences not only for enterprises and users, but also for cyber warfare between countries. Therefore, research to detect botnets is steadily progressing. However, the DGA-based botnet has a high detection rate with the existing signature and statistics-based technology, but also has a high limit in the false positive rate. Therefore, in this paper, we propose a detection model using text-based n-gram to detect DGA-based botnets. Through the proposed model, the detection rate, which is the limit of the existing detection technology, can be increased and the false positive rate can also be minimized. Through experiments on large-scale domain datasets and normal domains used in various DGA botnets, it was confirmed that the performance was superior to that of the existing model. It was confirmed that the false positive rate of the proposed model is less than 2 to 4%, and the overall detection accuracy and F1 score are both 97.5%. As such, it is expected that the detection and response capabilities of DGA-based botnets will be improved through the model proposed in this paper.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.59-66
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• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Journal of the Korean Regional Science Association
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• v.40 no.3
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• pp.23-42
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• 2024

This study examines changes in housing insecurity among young adults from a longitudinal perspective, recognizing the dynamic nature of young adulthood. The objective of the study is to explore shifts in housing insecurity and to identify the factors affecting entry into and exit from housing insecurity. Using data from the Seoul Youth Panel in 2021 and 2022, housing insecurity is measured across three dimensions, and changes over one year are categorized. The sample consists of 40% of individuals experiencing persistent security, 33% experiencing persistent insecurity, 14% exiting insecurity, and 13% entering security, indicating that the transition into and out of housing insecurity is quite dynamic. Empirical results from the logistic regression models reveal several key findings. Firstly, crises in employment and social domains significantly correlate shifts in housing insecurity among young people. Unstable employment and unsatisfactory job conditions increase the risk of entering, and decrease the likelihood of exiting housing insecurity. Social isolation and lower social support increase the risk of entry into housing insecurity, while higher social support enhances the likelihood of exiting housing insecurity. Secondly, residential characteristics play a pivotal role in the transition of housing insecurity. Those living in non-apartments and renters are considerably less likely to exit housing insecurity compared to those living in apartments and homeowners, respectively. Furthermore, residing in rooftop or semi-subterranean location, or undergoing residential moves, significantly elevate the risk of entering housing insecurity. Thirdly, external supports appear to have a limited role in achieving housing security for young adults. Parental economic resources significantly facilitate exiting housing insecurity, whereas governmental housing policy benefits show no significant effect. These findings provide important implications for policy-making aimed at addressing and preventing housing insecurity among young adults.

• Korean Journal of Adult Nursing
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• v.21 no.6
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• pp.652-665
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• 2009

Purpose: This study was conducted to identify job experiences of male hospital nurses. Methods: Data were collected from 20 male nurses working at general hospitals, through semi-structured in-depth interviews. The interviews were recorded and subsequently transcribed verbatim. Using content analysis, data were coded and categorized. Results: The analyzed domains were motivations for choosing nursing, occupational experiences (3 subdomains), and attitudes toward the future. A total of 85 significant statements were selected from the data and classified into 32 categories. The nurses' motivations for choosing nursing were advantages of employment, their aptitude, scarcity value of men, professionalism and job security, good promotion, stable income, and family influence. In occupational experiences, they were assigned to special fields and dissatisfied with vertical relationship, promotion system, their salary, and gaps in military service time; they had difficulties in adapting to female-dominated groups and encountered gender role stereotype and preconception; they were satisfied with their distinguished performance, but had damaged self-esteem, and were stressed and disappointed in their work. In their attitudes toward the future, they considered their career changes, but tried to make professional and personal advancement. Conclusion: These findings have implications for recruiting and retaining male nurses in clinical settings.