• Convergence Security Journal
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• v.15 no.7
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• pp.21-29
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• 2015

As the number of malicious Android applications increases rapidly, many automatic analysis systems are proposed. Hoping to trigger as many malicious behaviors as possible, the automatic analysis systems are adopting random touch generation modules. In this paper, we propose how to differentiate real human touches and randomly generated touches. Through experiments, we figured out that the distance between two consecutive human touches is shorter than that of random generation module. Also we found that the touch speed of human is also limited. In addition, humans rarely touch the outer area of smartphone screen. By using statistics of human smartphone touch, we developed an algorithm to differentiate between human touches and randomly generated touches. We hope this research will help enhance automatic Android app analysis systems.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.127-136
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• 2021

Real-time human recognition is a challenging task, as the images are captured in an unconstrained environment with different poses, makeups, and styles. This limitation is addressed by generating several facial images with poses, makeup, and styles with a single reference image of a person using Generative Adversarial Networks (GAN). In this paper, we propose deep learning-based human recognition using integration of GAN and Spatial Domain Techniques. A novel concept of human recognition based on face depiction approach by generating several dissimilar face images from single reference face image using Domain Transfer Generative Adversarial Networks (DT-GAN) combined with feature extraction techniques such as Local Binary Pattern (LBP) and Histogram is deliberated. The Euclidean Distance (ED) is used in the matching section for comparison of features to test the performance of the method. A database of millions of people with a single reference face image per person, instead of multiple reference face images, is created and saved on the centralized server, which helps to reduce memory load on the centralized server. It is noticed that the recognition accuracy is 100% for smaller size datasets and a little less accuracy for larger size datasets and also, results are compared with present methods to show the superiority of proposed method.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.220-225
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• 2021

Human population growth rate is an important parameter for real-world planning. Common approaches rely upon fixed parameters like human population, mortality rate, fertility rate, which is collected historically to determine the region's population growth rate. Literature does not provide a solution for areas with no historical knowledge. In such areas, machine learning can solve the problem, but a multitude of machine learning algorithm makes it difficult to determine the best approach. Further, the missing feature is a common real-world problem. Thus, it is essential to compare and select the machine learning techniques which provide the best and most robust in the presence of missing features. This study compares 17 machine learning techniques (base learners and ensemble learners) performance in predicting the human population growth rate of the country. Among the 17 machine learning techniques, random forest outperformed all the other techniques both in predictive performance and robustness towards missing features. Thus, the study successfully demonstrates and compares machine learning techniques to predict the human population growth rate in settings where historical data and feature information is not available. Further, the study provides the best machine learning algorithm for performing population growth rate prediction.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1129-1138
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• 2014

CAPTCHA is a technique which distinguishes human and machine using what human can judge easily but machine can't. Though Text-based-CAPTCHA has been widely used and can be implemented easily, it is less security than other CAPTCHAs such as image-based, or audio-based CAPTCHAs. To enhance the security of text-based CAPTCHA, many techniques have been developed. One of them is making CAPTCHA recognized hard using complex background or noise. In this paper, we introduce how to apply convolution filtering effectively to attack CAPTCHA and actually analyze Naver's CAPTCHA which has been used for joining a cafe with this method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.641-643
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• 2021

The Internet of Things (IoT) connects all markets and industries, enabling new business models for a variety of services and service providers. The Internet of Medical Things (IoMT) not only accelerates medical advances, but also enables treatment with a more human approach. In addition, it improves treatment methods and quality of precision medical care through data, enables timely treatment, and improves operational productivity of medical institutions through a simplified workflow. However, since the medical field directly affects human health and life, securing security has become an issue above all else, and is a target for hackers trying to exploit it. Therefore, in this study, IoMT technology and security threats and countermeasures in the medical field are analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1590-1593
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• 2005

Security defects occurring within corporate networks and the Internet may be abused by internal or external malicious attackers. Such abuses cause a financial toll through expenditures on additional human resources, the impact of down-time as problems are fixed, as well as damage from divulging corporate informational assets. Hence, through the precise analysis of the possible defects in network security and the identification of risks, preventative policy should be established to ensure maximum security. This report reviews methodologies that calculate and analyze levels of network security in order to resolve these problems, and generates appropriate test steps, test methods, and test items.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.4 no.4
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• pp.25-34
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• 1981

Recently there has been a marked increase in concern for security in computerized operations. The purposes of computer security controls are to protect against the unauthorized access to and modification of data processing resources, unauthorised access to and modification of data files and software, and the misuse of authorized activities. The controls relate to the physical security of the data processing department and of the areas within the data processing department : to the security of the data files, programs, and system software : and to the human interaction with the data files, programs, and system software. The controls that will be discussed in this paper include : I. Risk on the computer use. II. Methods of risk counter measure. III. Role of system auditing.

• Convergence Security Journal
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• v.13 no.2
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• pp.165-173
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• 2013

This thesis is the study of the analysis about Direction of Promote and Acquisition Program of Human Strength. Now we have question 'How we should develop the human resources program to gain human strength in the strategic environment of the future?' We know that if we don't estimate our project precisely, then we can't get good human resources. The purpose of this study is to find the way that how to gain excellent human resources now and in the future. The Ministry of National Defense to study US military Acquisition system. Korean military strategy in the situation of the confrontation between South and North Korea and in the situation of the international relationship and the way of constructing the military strength for the future. To improve Acquisition Program of Human Strength, we must develope and assess the future strategic environment of the Korean Peninsula especially Acquisition Program of Human Strength.

• Korean Security Journal
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• no.50
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• pp.145-172
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• 2017

In 2015 the Department of Education announced that it will make downsizing efforts by recommending classified downsizing ratio according to the evaluation of universities for active support toward autonomous efforts of universities with the possibilities of reform and qualitative structural reform for customized human resource cultivation according to the social demands. This is the preemtive structural reform preparing against the rapid decrease of the number of students, and the preparation for changing into competitive universities so that customized human resource that is needed in the society can be trained. Security Science Departments of Korea, first established in 1996, need changes in curriculum in order to prepare for the fourth revolution of the future, and are stagnant on the education goal and employment course. Therefore the adoption of related certificates, curriculum, NCS, and professional curriculum is needed. For example, Hansei University, Chung-Ang University, and Far East University have established the Department of Industrial Security, and Kyonggi University and Sungshin Women's University have established the Department of Convergence Security. Also, Konkuk University has established the Graduate School of Security and Disasters, the Graduate School of Information and Policy, the Graduate School of Criminal Justice, Gachon University the Graduate School of National Security, Sungkyunkwan University the Graduate School of Strategic Studies. This shows that the field of Security Science should not settle for itself. This article analyzes current curriculum and subjects of security, police, industrial security, military related academic departments of key universities. It is necessary to prepare for the future by predicting the change from the merge of academic departments and the demands of the times. As technical colleges are adopting NCS, this is the time to seek for systematic collaboration between universities and technical colleges and between industry, government, and academida.