• International journal of advanced smart convergence
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• v.5 no.4
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• pp.54-56
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• 2016

Code-reuse attacks are very dangerous in various systems. This is because they do not inject malicious codes into target systems, but reuse the instruction sequences in executable files or libraries of target systems. Moreover, code-reuse attacks could be more harmful to IoT systems in the sense that it may not be easy to devise efficient and effective mechanism for code-reuse attack detection in resource-restricted IoT devices. In this paper, we propose a detection scheme with using Kullback-Leibler (KL) divergence to combat against code-reuse attacks in IoT. Specifically, we detect code-reuse attacks by calculating KL divergence between the probability distributions of the packets that generate from IoT devices and contain code region addresses in memory system and the probability distributions of the packets that come to IoT devices and contain code region addresses in memory system, checking if the computed KL divergence is abnormal.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.47-56
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• 2023

Hydrogen energy is an eco-friendly energy that produces heat and electricity with high energy efficiency and does not emit harmful substances such as greenhouse gases and fine dust. In particular, smart hydrogen energy is an economical, sustainable, and safe future smart hydrogen energy service, which means a service that stably operates based on 'data' by digitally integrating hydrogen energy infrastructure. In this paper, in order to implement a data-based hydrogen charging station demand forecasting model, three hydrogen charging stations (Chuncheon, Sokcho, Pyeongchang) installed in Gangwon-do were selected, supply and demand data of hydrogen charging stations were secured, and 7 machine learning and deep learning algorithms were used. was selected to learn a model with a total of 27 types of input data (weather data + demand for hydrogen charging stations), and the model was evaluated with root mean square error (RMSE). Through this, this paper proposes a machine learning-based hydrogen charging station energy demand prediction model for optimal hydrogen energy supply and demand.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.34-39
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• 2006

This paper introduces a network security situation awareness tool using a traffic pattern map which facilitates recognizing a current network status by extracting and analyzing predetermined traffic features and displaying an abnormal or harmful traffic which deteriorates network performance. The traffic pattern-map consists of $26{\times}26$ intersections, on which the occupancy rate of the port having maximum occupancy is displayed as a bar graph. In general, in case of the Internet worm, the source address section on the traffic pattern map is activated. In case of DDoS the destination address section is activated.

• KIEAE Journal
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• v.10 no.6
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• pp.105-114
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• 2010

As children are known to touch and chew everything, green cleaning procedures are an important step in preventing children from ingesting harmful toxins. The objectives of this study are to develop a new, self-evaluation checklist and to suggest design recommendations which comply with easy, adaptable, economical ways to improve the eco-friendly indoor environment of Korean childcare facilities. The information compiled during this study was collected through literature review and internet surveys1) from July, 2009 to February, 2010. The results of this study show that the current Korean childcare accreditation system and practices emphasize clean building interiors, policies for sanitation and cleanliness, and control of humidity and lighting. On the other hand, the information provided by green-building rating systems from GBCC, LEED, and GBTool offers additional and comparative details regarding indoor environment quality and standards regarding the IAQ performance and management plan, ventilation and thermal comfort systems, views from windows, acoustics, and lighting. In conclusion, this document provides an appropriate and easy-to-follow, self-evaluation checklist composed of eight criteria and 51 practical items. This study also provides the design recommendations composed of 27 practical ideas focusing on interior elements. Both the checklist and design recommendations I have suggested can be a post-occupancy tool for evaluating eco-healthy facility standards as well as tips for continuing to maintain eco-healthy childcare facilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1754-1769
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• 2013

For the purpose of enhancing the spectrum efficiency, cognitive radio (CR) technology has been recently proposed as a promising dynamic spectrum allocation paradigm. In CR, spectrum sensing is the key capability of secondary users in a cognitive radio network that aims for reducing the probability of harmful interference with primary users. However, the individual CRs might not be able to carry out reliable detection of the presence of a primary radio due to the impact of channel fading or shadowing. This paper studies the cooperative spectrum sensing scheme as means of optimizing the sensing performance in AWGN and Rayleigh channels. Results generated from simulation provide evidence of the impact of channel condition on the complementary receiver operating characteristic (ROC). Based on the results, it was found that with constant local SNRs at the secondary users, the probability of missed detection ($P_m$) of cooperative spectrum sensing in a cognitive radio network, calculated using a closed form expression, can be significantly minimized. Thus, the paper illustrates that improvement of the detection performance of the CR network can be achieved by establishing a centralized cooperation among neighboring cognitive radio users. Finally, verification of the validity of the fusion schemes utilized for combining the individual CR decisions is provided.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.55-63
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• 2013

In cognitive radio networks, acquirement of position information of primary user is very important to secondary network since localization information of primary users can be utilized for improving the spectrum efficiency of secondary network and for avoiding harmful interference to primary users by using proper power control. Among various location methods, Received Signal Strength (RSS)-based localization has been widely used for distance measurements in the location detection process despite its inherent inaccuracy because it can be easily implemented without any additional hardware cost. In the RSS-based localization, the distance is measured by the received signal strength, and distance error can be caused by many factors such as fading, shadowing and obstacle between two nodes. In the paper, therefore we propose a localization scheme based on estimation of path-loss exponent to localize the location of primary users more accurately. Through simulations, it is shown that the proposed scheme can provide less localization error and interference rate to primary users than other schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.367-374
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• 2016

Recently, many people perform jobs including study and work within a common indoor space. Yet this space could have an adverse effect on operational efficiency as well as health because of many pollution factors. So maintaining a pleasant environment in the common space is important. In this thesis we study the integrated environment management system for better living conditions. This system analyzes and manages harmful environmental factors to make more pleasant environment in office, library or classroom. The proposed indoor environment management system will provide a pleasant environment by monitoring the indoor environment and driving the actuator in real time. In addition, it can be applicable to different types of indoor space to reach solutions to raise recognition of indoor environment pollution by people.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.493-498
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• 2005

P2P service is a method that can share various information through direct connection between computer of a person who have information and a Person who have information without server in the Internet and it is getting a lot of popularity by method for free ex change of file. P2P file sharing systems have become popular as a new paradigm for information exchange. Because all users who use service in P2P file sharing system can use shared files of several users freely by equal access privilege, it is happening the 'free rider' that only download shared file of other users without share own files. Although a user share a malicious file including virus, worm or file that have title differing with actuality contents, can use file sharing service without limitation. In this paper, we propose a method that restrict access of 'free rider' that only download using reputation information that indicate reliability of user. Also, we restrict usage ons hared file of other users about users who share harmful file.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.143-151
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• 2016

Many people interested in indoor air quality monitoring since they spend a majority of their time indoors such as homes and offices. This paper proposes the effective indoor air quality monitoring system and it can gauge carbon dioxide, particulate matter and VOCs(Volatile Organic Compounds) which can be harmful to humans. The proposed system is composed of three main modules which are device, web server, and mobile application. In order to evaluate the performance, we tested two cases which are candle and smoke. We monitor the condition of indoor air quality with our mobile application. Also, we developed the information graphics to compare the condition of air quality between indoor and outdoor and this mobile application improves usability.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.