• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.449-455
• /
• 2011

Illegal transportation act using a private truck cases indigested freight market. Moreover it incurs social and economic damage. There are some remedy for this problem that is reintroducing suspension of the service law, creating the law to punish client who have the goods which is delivered and improving transportation environment.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.4
• /
• pp.119-125
• /
• 2013

The amount of digital content grows exponentially by the development of the internet and the change of computing environments and the target also is getting wider. The industry using this digital content has been growing greatly. However, the distribution of pirated digital content is increasing using internet because digital content is easy to store and transmit and the damage is growing. In this paper, we propose safety trading system which can conceal the author's information safely in digital content in order to block illegal distribution of digital content. ARIA encryption algorithm is used to protect the concealed information of author in digital content and it is a help to track the illegal traders by doing fingerprinting of buyer information to digital content and managing the transaction information. The technical support for copyright dispute is to allow by providing the capability to verify illegal edit to original digital contents.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.3
• /
• pp.147-156
• /
• 2012

Most people in our society use credit card instead of cash or check, so credit card is very important economic method. Credit card supposed to be safe, but hackers hack credit card for illegal deal. Also hackers make fake credit card and issue fake credit card to other people. In this thesis it will study and analyze damage case for safe credit card deal. It will use safe credit card system to insert variety of information and data of using pattern in artificial intelligence network, so print out the possibility of risk and monitor the risk of credit card user's deal pattern, so if one of user's pattern is different than normal pattern, it will pop up message in consultant's screen. This thesis will study and suggest way of prevent from illegal deal and user friendly credit card checking system.

• Animal Systematics, Evolution and Diversity
• /
• v.36 no.3
• /
• pp.216-221
• /
• 2020

Parrots are common targets for illegal trade because of their beauty and high price. Accurate identification is necessary for the prevention of illegal trade and conservation of parrots. In the present study, mitochondrial markers of cytochrome b (CYTB) gene were used to identify parrot species from Korean zoos. Totally, 27 samples were collected from Seoul Zoo, Cheongju Zoo, and Uchi Zoo. After collection, total DNA of samples was extracted and used for PCR amplification. CYTB fragments were sequenced from all samples examined. The obtained sequences were used for GenBank blast, distance estimation, and phylogenetic analysis. All species were identified using CYTB sequences that determined 27 samples belong to 13 species in 7 genera, and 3 families. Our finding demonstrated the usefulness of CYTB sequences for identifying parrot species in Korean zoos.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.565-568
• /
• 2016

Recently, the number of illegal parking is increasing as the number of cars are increasing. Especially, people who use residential parking permit program are in trouble because of illegal parking. The most typical example is that people who use residential parking permit are damaged in expense, etc and various social issues such as legal actions are caused by illegal parking. In this paper, we discuss about the arduino design for the system and uploading the location information to use the location information for a parking system.

• The Journal of the Korea Contents Association
• /
• v.16 no.8
• /
• pp.97-106
• /
• 2016

The results of advanced studies which handled the relationship between social norm and intention to use illegal download don't match exactly. This study determined that the reason why the results of advanced studies are confused is, that moderator variables play important roles. For this reason, this study planned to test for significance of moderators consisting of attitude to copyright law(A) and perceived price importance at time of purchase(B). To achieve this, the present study divide social norm into two norms(subjective norm and group norm) and set up hypotheses on the moderating effects of two variables(A, B) between these two norms and intention to use the illegal download. The results show that all but one hypotheses are accepted. The other moderating effect hypothesis which is consist of subjective norm and attitude toward copyright law is rejected. This means that the effect of group norm on intention to use illegal download is moderated by attitude to copyright law. Also, this result means the effects of group/subjective norm on intention to use illegal download is moderated by the perceived price importance at time of purchase.

• Convergence Security Journal
• /
• v.21 no.2
• /
• pp.11-18
• /
• 2021

To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.8
• /
• pp.21-30
• /
• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

• Convergence Security Journal
• /
• v.23 no.2
• /
• pp.47-54
• /
• 2023

The global popularity of K-content(Korean Wave) has led to a continuous increase in copyright infringement cases involving domestic works, not only within the country but also overseas. In response to this trend, there is active research on technologies for detecting illegal distribution sites of domestic copyrighted materials, with recent studies utilizing the characteristics of domestic illegal distribution sites that often include a significant number of advertising banners. However, the application of detection techniques similar to those used domestically is limited for overseas illegal distribution sites. These sites may not include advertising banners or may have significantly fewer ads compared to domestic sites, making the application of detection technologies used domestically challenging. In this study, we propose a detection technique based on the similarity comparison of links and text trees, leveraging the characteristic of including illegal sharing posts and images of copyrighted materials in a similar hierarchical structure. Additionally, to accurately compare the similarity of large-scale trees composed of a massive number of links, we utilize Graph Neural Network (GNN). The experiments conducted in this study demonstrated a high accuracy rate of over 95% in classifying regular sites and sites involved in the illegal distribution of copyrighted materials. Applying this algorithm to automate the detection of illegal distribution sites is expected to enable swift responses to copyright infringements.

• 한국정보통신설비학회:학술대회논문집
• /
• 2009.08a
• /
• pp.108-111
• /
• 2009

In this paper, both various content filtering methods and technological trends are briefly reviewed. A novel method is provided for preventing the illegal copies of copyright IPTV contents from being propagated through the P2P sites and web harddisk services.