• Analytical Science and Technology
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• v.19 no.1
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• pp.58-64
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• 2006

A mugwort-tissue-based modified carbon paste electrode was constructed for the amperometric detection of hydrogen peroxide and its electrochemical properties are described. Especially the amperometric signal was very stable and bigger than any other enzyme electrode studied in this lab. The effect of tissue composition on the response was linear within the wide range of experiment and the linearity of Lineweaver-Burk plot showed that the sensing process of the biosensor is by enzymatic catalysis. And pH dependent current profile connoted that two isozymes are active in this system.

• Journal of The Korean Association of Information Education
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• v.12 no.2
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• pp.183-194
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• 2008

This research was conducted from the perspective of student management focusing on such central topic as realization of research ethics on the basis of research ethics case study model. In this study, improvement method for research ethics education through means of application of DEVAC System, which is a paper plagiarism detection system, and survey on current status of research ethics in college education and degree of consciousness thereof were explored. Through these investigations, a topic relating to establishment of the foundation in order to foster consciousness of research ethics in the college education was established as the primary purpose of this study. To accomplish the purpose of this study, firstly, actual situation of paper plagiarism committed by the college students and their consciousness were surveyed. Secondly, the research ethics education was examined through means of applying DEVAC paper plagiarism detection system. The results from investigations revealed the followings: First, 424 students (65.43%) who participated in this research and survey on the fact of paper plagiarism had experience of report plagiarism, and the result of investigation showed that 49.3% of students among those who had experience of paper plagiarism committed report plagiarism more than three times in a semester. And, 34.1% of participants showed a positive response to the use of a paper plagiarism detection system in the college, and results from the investigation displayed that the creative education (39.0%) marked the highest scores as in the educational method to reinforce the research ethics. Second, the results from examination of paper plagiarism having applied DEVAC system indicated that use of this system can be an alternative to prevent paper plagiarism from students. It is realized through this study that there is a necessity in various respects to build up the foundation which will enable individual students to improve their consciousness to such a degree so as to make them clearly recognize the fact that plagiarism is criminal act.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.439-449
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• 2024

Recent rapid advancements in voice generation technology have enabled the natural synthesis of voices using text alone. However, this progress has led to an increase in malicious activities, such as voice phishing (voishing), where generated voices are exploited for criminal purposes. Numerous models have been developed to detect the presence of synthesized voices, typically by extracting features from the voice and using these features to determine the likelihood of voice generation.This paper proposes a new model for extracting voice features to address misuse cases arising from generated voices. It utilizes a deep learning-based audio codec model and the pre-trained natural language processing model BERT to extract novel voice features. To assess the suitability of the proposed voice feature extraction model for voice detection, four generated voice detection models were created using the extracted features, and performance evaluations were conducted. For performance comparison, three voice detection models based on Deepfeature proposed in previous studies were evaluated against other models in terms of accuracy and EER. The model proposed in this paper achieved an accuracy of 88.08%and a low EER of 11.79%, outperforming the existing models. These results confirm that the voice feature extraction method introduced in this paper can be an effective tool for distinguishing between generated and real voices.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.67-73
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• 2017

In this study, we mainly inquired into structural reforms of the current legal system that could minimize the side effects and protect financial customers as the use of AI robo-advisor were increasing. First, regarding a specific reform, it is necessary to introduce and establish a rapid detection system for unusual transactions by the Robo-advisor management company, the strict liability of the management company, the management company's mandatory obligation to obtain indemnity insurance, and limited criminal penalties. Furthermore, it is necessary to establish a comprehensive basic law regarding AI. In this basic law, the promotion of the development of AI technology and the minimization of side effects should be dealt with in harmony with each other. Like the approach of this study, we hope that similarly detailed and practical discussions will be made on the AI era from various perspectives in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.51-61
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• 2009

Recently, the cyber-attacks using botnets are being increased, Because these attacks pursue the money, the criminal aspect is also being increased, There are spreading of spam mail, DDoS(Distributed Denial of Service) attacks, propagations of malicious codes and malwares, phishings. leaks of sensitive informations as cyber-attacks that used botnets. There are many studies about detection and mitigation techniques against centralized botnets, namely IRC and HITP botnets. However, P2P botnets are still in an early stage of their studies. In this paper, we analyzed the traffics of the Peacomm bot that is one of P2P-based storm bot by using honeynet which is utilized in active analysis of network attacks. As a result, we could see that the Peacomm bot sends a large number of UDP packets to the zombies in wide network through P2P. Furthermore, we could know that the Peacomm bot makes the scale of botnet maintained and extended through these results. We expect that these results are used as a basis of detection and mitigation techniques against P2P botnets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• Analytical Science and Technology
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• v.21 no.3
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• pp.212-221
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• 2008

In order to investigate the information for effective detection and developing of latent fingerprints, we identified fatty acids composition of latent fingerprints on non-porous evidence surface and the chemical changes of latent fingerprint residue after print deposition during 7 months. Fingerprints from eight Korean male donors (aged 29-50 years) and one female donor (aged 36 years) were collected. All fingerprints were found to contain lauric acid (C12:0), myristic acid (C14:0), palmitic acid (C16:0), stearic acid (C18:0), elaidic acid (C18:1n9t), oleic acid (C18:1n9c), linoleic acid (C18:2n6c), arachidic acid (C20:0), linolenic acid (C18:3n3), erucic acid (C22:1n9) and docosadienoic acid (C22:2) and primarily palmitic acid (35.45-48.37%), oleic acid (14.84-28.49%), stearic acid (9.71-24.96%) and linoleic acid (7.68-18.8%) occupied 75% of total fatty acids. When the fingerprints were deposited at dark room for 7 months, total fatty acids components decreased about 12-25%. It can be explained that significant degradation of long-chain fatty acids such as elaidic acid (C18:1n9t), arachidic acid (C20:0), linolenic acid (C18:3n3), erucic acid (C22:1n9), and docosadienoic acid (C22:2) resulted in the generation of myristic acid (C14:0), myristoleic acid (C14:1) and pentadecanoic acid (C15:0).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.675-678
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• 2018

Since the face has a unique property to identify human, the face recognition is actively used in a security area and an authentication area such as access control, criminal search, and CCTV. The frontal face image has the most face information. Therefore, it is necessary to acquire the front face image as much as possible for face recognition. In this study, the face region is detected using the Adaboost algorithm using Haar-like feature and tracks it using the mean-shifting algorithm. Then, the feature points of the facial elements such as the eyes and the mouth are extracted from the face region, and the ratio of the two eyes and degree of rotation of the face is calculated using their geographical information, and the approximate front face image is presented in real time.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.61-72
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• 2020

The fear of crime, discussed in the early 1960s in the United States, is a psychological response, such as anxiety or concern about crime, the potential victim of a crime. These anxiety factors lead to the burden of the individual in securing the psychological stability and indirect costs of the crime against the society. Fear of crime is not a good thing, and it is a part that needs to be adjusted so that it cannot be exaggerated and distorted by the policy together with the crime coping and resolution. This is because fear of crime has as much harm as damage caused by criminal act. Eric Pawson has argued that the popular impression of violent crime is not formed because of media reports, but by official statistics. Therefore, the police should watch and analyze news related to fear of crime to reduce the social cost of fear of crime and prepare a preemptive response policy before the people have 'fear of crime'. In this paper, we propose a deep - based news classification system that helps police cope with crimes related to crimes reported in the media efficiently and quickly and precisely. The goal is to establish a system that can quickly identify changes in security issues that are rapidly increasing by categorizing news related to crime among news articles. To construct the system, crime data was learned so that news could be classified according to the type of crime. Deep learning was applied by using Google tensor flow. In the future, it is necessary to continue research on the importance of keyword according to early detection of issues that are rapidly increasing by crime type and the power of the press, and it is also necessary to constantly supplement crime related corpus.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.199-207
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• 2013

Recently, hacking is seen as a criminal activity beyond an activity associated with curiosity in the beginning. The malignant bot which is used as an attack technique is one of the examples. Malignant Bot is one of IRC Bots and it leaks user's information with attacker's command by attacking specified IP range. This paper will discuss an access method and a movement process by analyzing shadowbot which is a kind of a malignant Bot and will suggest possible countermeasure. This study has two distinct features. First, we analyze malignant Bot by analyzing tools such as VM ware. Second, we formulate a hypothesis and will suggest possible countermeasure through analyzing malignant Bot's access method and movement. Performance evaluation will be conducted by applying possible countermeasure to see if it can prevent attacks from malignant bot.