• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1726-1743
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• 2014

DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker's intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.193-198
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• 2018

In Korea, the penetration rate of Internet, telephone and smart devices is reaching the highest level in the world. Cyber financial crimes that exploit such infrastructures continue to evolve. Since the first Voice Phishing crime in May 2006, ten years later, there has been a constant occurrence of Voice Phishing crime. Voice Phishing is a crime in which a victim is phoned for false information to figure out the victim's account number and password. This method of Voice Phishing evolves day by day, and it is difficult to investigate. Most of Voice Phishing is a form of international organized crime that is based in Southeast Asia such as China, and it is not easy to eradicate by international cooperation investigation. The purpose of this study is to investigate the actual situation and case analysis of Voice Phishing crime, and to propose the countermeasures against police Voice Phishing counterplan.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.93-100
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• 2022

Korea's ancestral culture has limited travel and contact due to Corona (COVID-19). In addition, Korean ancestral culture meets in person to commemorate the deceased. In this paper, we propose a non-face-to-face metaverse memorial platform service that can commemorate the deceased and perform ancestral rites in the cyber world (virtual reality) by applying the metaverse technology. The services proposed in the study consisted of a remembrance hall that displays the life story of the deceased, a ancestral hall that conducts ancestral rites for the deceased, and a deceased pavilion that checks the remains and wills of the deceased. In addition, the virtual reality device (HMD: Head Mounted Display) set the teleportation and content resolution to 4K to minimize dizziness. In particular, the priests applied interaction technology to provide an immersive service for ancestral rites between family members. The researched memorial hall metaverse service is a metaverse-based platform service that allows anyone to commemorate the deceased as a family unit in a non-face-to-face state rather than face-to-face.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.1-12
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• 2023

It is very time-intensive to obtain data with labels on anomaly detection tasks for multivariate time series. Therefore, several studies have been conducted on unsupervised learning that does not require any labels. However, a well-done integrative survey has not been conducted on in-depth discussion of learning architecture and property for multivariate time series anomaly detection. This study aims to explore the characteristic of well-known architectures in anomaly detection of multivariate time series. Additionally, architecture was categorized by using top-down and bottom-up approaches. In order toconsider real-world anomaly detection situation, we trained models with dataset such as power grids or Cyber Physical Systems that contains realistic anomalies. From experimental results, we compared and analyzed the comprehensive performance of each architecture. Quantitative performance were measured using precision, recall, and F1 scores.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.39-46
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• 2024

Many researchers make efforts to evaluate water quality using various models. Such models require a dataset without missing values, but in real world, most datasets include missing values for various reasons. Simple deletion of samples having missing value(s) could distort distribution of the underlying data and pose a significant risk of biasing the model's inference when the missing mechanism is not MCAR. In this study, to explore the most appropriate technique for handing missing values in water quality data, several imputation techniques were experimented based on existing KNN and MICE imputation with/without the generative neural network model, Autoencoder(AE) and Denoising Autoencoder(DAE). The results shows that KNN and MICE combined imputation without generative networks provides the closest estimated values to the true values. When evaluating binary classification models based on support vector machine and ensemble algorithms after applying the combined imputation technique to the observed water quality dataset with missing values, it shows better performance in terms of Accuracy, F1 score, RoC-AuC score and MCC compared to those evaluated after deleting samples having missing values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.289-295
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• 2020

The purpose of this study is to investigate the difference of learners' preference for animation movies in EFL English classes. In this study, four classes of 124 college students that participated in the English screen class employed an animation, Alice in Wonderland. This study examined the different activities of three categories of pre-study, while-study, and post-study. First, on the analysis of studying activities of 15 items, the results showed meaningful differences depending on the students' gender. That is, female students were more interested in mostly all of the activities, while male students' interests were skewed to some post-study activities. Second, comparing the differences of studying interest among the three groups, the low group is more concerned with the pre-study activities, while the higher group is generally interested in the while studying and post-study activities. Third, on the analysis of correlation between the three level groups and activities, the results indicated meaningful differences in some activities. In summary, based on the results of this research, it is necessary to consider the learners' variables and focus on the learners in the English screen class. Further, teachers should apply these results to the management of their screen class and to the development of teaching materials.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.93-107
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• 2019

The open data portal collects data created by public institutions and opens and shares them according to related laws. With the activation of the Fourth Industrial Revolution, all sectors of our society are demanding high quality data, but the data required by the industry has not been greatly utilized due to the lack of quantity and quality. Numerous data collected in the real world can be implemented in cyber physical systems to simulate real-world problems, and alternatives to various social issues can be found. There is a limit to being provided. Location intelligence is a technology that enables existing data to be represented in space, enabling new value creation through convergence. In this study, to present location intelligence of open data, we surveyed the status of location information by data in open data portal. As a result, about 60% of the surveyed data had location information and the representative type was address. Appeared. Therefore, by suggesting location intelligence of open data based on address and how to use it, this study aimed to suggest a way that open data can play a role in creating future social data-based industry and policy establishment.

• Archives of design research
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• v.14 no.3
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• pp.145-154
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• 2001

These days, the products like Walkman, mobile phone, notebook PC, PDA are moving together with our body, and in the imaginary world like internet, our other self, Avatar is moving in place of our body on the cyber world. These products are related with our human body, and when considering the ones, attached to the human body, and having the meaning of mental combination like these, as the combination of the human and the products, it is necessary to examine these products in approaching them with respect to the combination relation between the human and the products. As a result of examining we can understand that the products, said to combine with the human body, are coming oui steadily. and recently, the inclination on the combination and the movement appears strongly. As this background, there are a breakdown of dichotomy thought, mixed sexual imitation, cyber culture, techno culture. concept of informative nomands, phenomenon which the division of human and machine becomes vague. and the miniaturization of products. imitation of human, phenomenon that the Inclination on the combination with human is more accelerated by networking. These products combine with human body at each wearing type in the various forms. Its functions become multi-layered, and closer to the human body physically. or its communication becomes high·graded and, they have the recombined form through the existing products which the human has And, they communicate each other. have the strong fashionable property, and the characteristics like the imaginary product to imitate the human body and substitute for the human behave.

• Korean Security Journal
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• no.61
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• pp.59-85
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• 2019

In the reality that the boundary between the real world and the virtual world disappears with the 4th Industrial Revolution, cyber crimes that occur beyond time and space have clear limitations in fulfilling their duties only with the police force of government organizations established under the real law system. The research method of this thesis is based on the literature research and the experience of security work. The purpose of this paper is to establish a social system where collective intelligence of each social field can participate voluntarily to respond to cyber crimes occurring beyond the time and space before the law and institutionalization. In addition, the social system in which collective intelligence in each social sector can participate voluntarily was established to define crime types in cyberspace in real time and to prevent crimes defined by the people themselves and the counter-measures had been proposed in order to form social consensus. First, it is necessary to establish a collective intelligent network-type cyberpolice volunteer system. The organization consists of professors of security and security related departments at universities nationwide, retired public officials from the National Intelligence Service, the National Police Agency, and the National Emergency Management Agency, security companies and the organizations, civilian investigators, security & guard, firefighting, police, transportation, intelligence, security, national security, and research experts. Second, private sector regulation should be established newly under the Security Business Act. Third, the safety guard of the collective intelligent cyberpolice volunteer system for the stability of the people's lives should strengthen volunteer work. Fourth, research lessons and legal countermeasures against cybercrime in advanced countries should be introduced. Fifth, the Act on the Protection of Personal Information, the Act on Promotion of Information and Communication Network Utilization and Information Protection, the Act on the Utilization and Protection of Credit Information, and the Special Act on the Materials and Parts Industry should be amended. Sixth, police officers should develop cybercrime awareness skills for proactive prevention activities.