• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2002.11a
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• pp.137-142
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• 2002

The purpose of this study was to examine the features that make residents feel “at home” in ALFs in Southwest Virginia and to suggest further policy and design guidelines for better Quality of ALFs as a “home.” For this purpose, residents' needs, experiences, and opinions of the physical environment, the social environment, and the organizational environments such as policies and programs of ALFs were identified. As a multi-case study, five ALFs in Southwest Virginia were studied using constant comparative methos of data analysis. In addition to face-to-face interviews with 25 residents and five administrators of five ALFs, observations were conducted with personal journal. Overall, the five sites selected presented homelike features showing the philosophy of assisted living which combines housing and services. Each facility was designed to be a single-family house or multi-family dwelling in outside appearance. As a whole, residents felt isolation and loneliness and they did not have active interaction with other residents because of diverse background among the residents. However, all of them had close relationships with the staff. The staff's attitude and behavior seemed to influence greatly the residents' feeling “at home.” Despite the provision of diverse activities by the facilities, many residents did not participate in the programs. Most of the residents agreed that the rule and regulations were fair. In spite of high satisfaction with the facility, many people did not think of their current dwelling as a real ‘home.’ As the biggest difference between living in their own homes and living in the ALF, people pointed out a lack of independence, freedom, and autonomy. Residents of ALFs may have reordered their priorities in their current life situation so that safety, security, and care were more important to them than feeling “at home.” Among the three factors --physical, social, and organizational-- that affect the residents' perception of ALFs as a “home, ” many emphasized the importance of social factors such as relationships with the staff and residents, and social support from their family or friends.

• The KIPS Transactions:PartC
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• v.9C no.6
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• pp.831-840
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• 2002

Due to the advance of computer and communication technology, intrusions or crimes using a computer have been increased rapidly while tremendous information has been provided to users conveniently Specially, for the security of a database which stores important information such as the private information of a customer or the secret information of a company, several basic suity methods of a database management system itself or conventional misuse detection methods have been used. However, a problem caused by abusing the authority of an internal user such as the drain of secret information is more serious than the breakdown of a system by an external intruder. Therefore, in order to maintain the sorority of a database effectively, an anomaly defection technique is necessary. This paper proposes a method that generates the normal behavior profile of a user from the database log of the user based on an association mining method. For this purpose, the Information of a database log is structured by a semantically organized pattern tree. Consequently, an online transaction of a user is compared with the profile of the user, so that any anomaly can be effectively detected.

• Tunnel and Underground Space
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• v.23 no.3
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• pp.192-202
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• 2013

The domestic demand of natural gas has increased continuously due to the sudden rise of oil price and regulations on greenhouse gas to global warming. In order to improve the supply security of natural gas market in Korea, the agreement on supply of pipeline natural gas (PNG) in Russia was signed between Gazprom and Korea Gas Corporation in 2008. If the supply plan of Russian natural gas is realized, underground storage facilities would be required in order to balance supply and demand of natural gas because the gas demand is concentrated in the winter. This study investigated the safety of the storage facility in quantitative way considering several design parameters such as gas pressure, depth of the storage cavern, rock condition and in-situ horizontal stress ratio. Two dimensional stress analyses were conducted using axi- symmetry condition to examine the behavior of cavern depending upon suggested design parameters. Results showed that the factor of safety, defined as the ratio of 'shear strength'/'shear stress', was largely affected by the depth, rock class and gas pressure but was insensitive to the coefficient of lateral pressure(Ko).

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.1-8
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• 2021

With the rapid increase in the use of IoT and mobile devices, cyber criminals targeting IoT devices are also on the rise. Among IoT devices, when using a wireless access point (AP), problems such as packets being exposed to the outside due to their own security vulnerabilities or easily infected with malicious codes such as bots, causing DDoS attack traffic, are being discovered. Therefore, in this study, in order to actively respond to cyber attacks targeting IoT devices that are rapidly increasing in recent years, we proposed a method to collect traces of intrusion incidents artifacts from IoT devices, and to improve the validity of intrusion analysis data. Specifically, we presented a method to acquire and analyze digital forensics artifacts in the compromised system after identifying the causes of vulnerabilities by reproducing the behavior of the sample IoT malware. Accordingly, it is expected that it will be possible to establish a system that can efficiently detect intrusion incidents on targeting large-scale IoT devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.903-909
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• 2021

Caenorhabditis elegans whose DNA sequence was completely identified is a representative species used in various research fields such as gene functional analysis and animal behavioral research. In the mean time, many researches on the bio-monitoring system to determine whether water is contaminated or not by using the swimming activities of nematodes. In this paper, we show the possibility of using the swimming activities of C. elegans in the development of a machine learning based bio-monitoring system which identifies chemicals that cause water pollution. To characterize swimming activities of nematode, BLS entropy is computed for the nematode in a frame. And, BLS entropy profile, an assembly of entropies, are classified into several patterns using clustering algorithms. Finally these patterns are used to construct data sets. We recorded images of swimming behavior of nematodes in the arenas in which formaldehyde, benzene and toluene were added at a concentration of 0.1 ppm, respectively, and evaluate the performance of the developed HMM.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.429-438
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• 2018

Recently, there has been a tendency for accidents occurring in manufacturing to lead to serious accidents and serious industrial accidents and to extend to community disasters. In accordance with the Third Plan (2015-2019) of the National Security Management Plan, the Safety Administration announces and promotes improvement measures to minimize industrial accidents and disasters. In the case of industrial accidents from KOSHA 2015 to 2017, the accident rate of the metal-related manufacturing industry is 1.57%, which is more than three times higher than the average 0.50% of all industries. As a result of investigating the causes of disasters, 72% of workers were found to be caused by unsafe behaviors. In addition, insecure behaviors are closely related to safety consciousness, and a survey on safety consciousness was conducted for workers in this field. Safety consciousness improvement has the affirmative effect on accident prevention and it is a factor to reduce accidents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1311-1319
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• 2019

Currently, the web environment is a commonly used area for sharing information and conducting business. It is becoming an attack point for external hacking targeting on personal information leakage or system failure. Conventional signature-based detection is used in cyber threat but signature-based detection has a limitation that it is difficult to detect the pattern when it is changed like polymorphism. In particular, injection attack is known to the most critical security risks based on web vulnerabilities and various variants are possible at any time. In this paper, we propose a novelty detection technique to detect abnormal state that deviates from the normal state on web-server log dataset(WSLD). The proposed method is a machine learning-based technique to detect a minor anomalous data that tends to be different from a large number of normal data after replacing strings in web-server log dataset with vectors using machine learning-based embedding algorithm.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.45-52
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• 2021

Although many studies have been conducted to identify unknown attacks in cyber security intrusion detection systems, studies based on outliers are attracting attention. Accordingly, we identify outliers by defining categories for unknown attacks. The unknown attacks were investigated in two categories: first, there are factors that generate variant attacks, and second, studies that classify them into new types. We have conducted outlier studies that can identify similar data, such as variants, in the category of studies that generate variant attacks. The big problem of identifying anomalies in the intrusion detection system is that normal and aggressive behavior share the same space. For this, we applied a technique that can be divided into clear types for normal and attack by discrete wavelet transformation and detected anomalies. As a result, we confirmed that the outliers can be identified through One-Class SVM in the data reconstructed by discrete wavelet transform.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.70-78
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• 2021

It is true that the police have been faithful to the role of the regime's sewer and committed many disruptions and errors, and have been criticized and criticized by the public. It should now be the foundation of the democratic police and an organization supported by the people. The problem is that the quality, personality, and values of 130,000 police officers should be changed and should be in line with the spirit of the times. One of the theories of police corruption is the "rotten apple hypothesis." The theory is that there is a high possibility that the entire police force will be corrupted, as if the defective apple in the apple box is rotten and the whole apple is rotten, without filtering out potential corrupt police officers during the recruitment phase. In other words, the cause of corruption is based on personal flaws. This study intends to analyze the causes of police corruption and improvement measures. The purpose of this study is to ensure that police officers in charge of national security are usually armed with ethics and good conduct. The police should be trusted by the people and need a stronger prescription for police corruption. In this respect, this study aims to solve the corruption problem of police officials, analyze anti-corruption, and find out what are the desirable countermeasures. The main study methods of this study are as follows; First, we first tried to collect data through research on corruption-related literature. The analysis was focused on the related papers of police corruption and government reports. Second, police corruption theory and anti-corruption alternatives were analyzed. It was reviewed focusing on the theory of corruption or translated data. Third, a literature survey was analyzed to examine the National Police Agency's perception of police corruption. Based on these research methods, we tried to derive the desirable control measures for the hypothesis of police corruption. This study is believed to have contributed to supporting the organizational corruption and culture of the apple box, including the personality of the individual's values, which is a rotten apple theory of police corruption.

• Journal of IKEEE
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• v.26 no.3
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• pp.380-388
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• 2022

The traditional malware detection technologies collect known malicious programs and analyze their characteristics. Then such a detection technology makes a blacklist based on the analyzed malicious characteristics and checks programs in the user's system based on the blacklist to determine whether each program is malware. However, such an approach can detect known malicious programs, but responding to unknown or variant malware is challenging. In addition, since such detection technologies generally monitor all programs in the system in real-time, there is a disadvantage that they can degrade the system performance. In order to solve such problems, various methods have been proposed to analyze major behaviors of malicious programs and to respond to them. The main characteristic of ransomware is to access and encrypt the user's file. So, a new approach is to produce the whitelist of programs installed in the user's system and allow the only programs listed on the whitelist to access the user's files. However, although it applies such an approach, attackers can still perform malicious behavior by performing a DLL(Dynamic-Link Library) injection attack on a regular program registered on the whitelist. This paper proposes a method to respond effectively to attacks using DLL injection.