• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.297-303
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• 2021

When sound waves propagate over long distances in shallow water, measured transmission loss is greater than predicted one using underwater acoustic model with the Rayleigh reflection model due to inhomogeneity of the bottom. Accordingly, the US Navy predicts sound wave propagation by applying the empirical formula-based High Frequency Bottom Loss (HFBL) model. In this study, the measurement and analysis of transmission loss was conducted using mid-frequency (2.3 kHz, 3 kHz) in the shallow water of the East Sea in summer. BELLHOP eigenray tracing output shows that only sound waves with lower grazing angle than the critical angle propagate long distances for several kilometers or more, and the difference between the predicted transmission loss based on the Rayleigh reflection model and the measured transmission loss tend to increase along the propagation range. By comparing the Rayleigh reflection model and the HFBL model at the high grazing angle region, the bottom province, the input value of the HFBL model, is estimated and BELLHOP transmission loss with HFBL model is compared to measured transmission loss. As a result, it agrees well with the measurements of transmission loss.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.203-215
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• 2022

The study is to investigate research trends and knowledge structures in the Smart Farm field. To achieve the research purpose, keywords and the relationship among keywords were analyzed targeting 104 Korean academic journals related to the Smart Farm in KCI(Korea Citation Index), and topics were analyzed using the LDA Topic Modeling technique. As a result of the analysis, the main keywords in the Korean Smart Farm-related research field were 'environment', 'system', 'use', 'technology', 'cultivation', etc. The results of Degree, Betweenness, and Eigenvector Centrality were presented. There were 7 topics, such as 'Introduction analysis of Smart Farm', 'Eco-friendly Smart Farm and economic efficiency of Smart Farm', 'Smart Farm platform design', 'Smart Farm production optimization', 'Smart Farm ecosystem', 'Smart Farm system implementation', and 'Government policy for Smart Farm' in the results of Topic Modeling. This study will be expected to serve as basic data for policy development necessary to advance Korean Smart Farm research in the future by examining research trends related to Korean Smart Farm.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.1-14
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• 2022

This study tried to suggest crisis management compliance to prevent personal information infringement accidents that may occur in the process because the data including personal information is being processed in the artificial intelligence (AI) service process. To this end, first, the AI service provision process is divided into 3 processes such as service planning/data design and collection process, data pre-processing and purification process, and algorithm development and utilization process. And 3 processes are subdivided into 9 stages following to personal information processing stages to infringe personal information. All processes were investigated with literature and experts' Delphi. Second, the investigated personal information infringement factors were selected through FGI, Delphi, etc. for experts. Third, a survey was conducted with experts on the severity and possibility of each personal information infringement factor, and the validity and adequacy of the 94 responses were verified. Fourth, to present appropriate risk management compliance for personal information infringement factors in AI services, a method for calculating the risk level of personal information infringement is prepared by utilizing the asset value of personal information, personal information infringement factors, and the possibility of infringement accidents. Through this, the countermeasures for personal information infringement incidents were suggested according to the scored risk level.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.115-127
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• 2021

With the development of science and technology around the world, the realm of cyberspace, following land, sea, air, and space, is also recognized as a battlefield area. Accordingly, it is necessary to design and establish various elements such as definitions, systems, procedures, and plans for not only physical operations in land, sea, air, and space but also cyber operations in cyberspace. In this research, the importance of cyber targets that can be considered when prioritizing the list of cyber targets selected through intermediate target development in the target development and prioritization stage of targeting processing of cyber operations was selected as a factor to be considered. We propose a method to calculate the score for the cyber target and use it as a part of the cyber target prioritization score. Accordingly, in the cyber target prioritization process, the cyber target importance category is set, and the cyber target importance concept and reference item are derived. We propose a TIR (Target Importance Rank) algorithm that synthesizes parameters such as Event Prioritization Framework based on PageRank algorithm for score calculation and synthesis for each derived standard item. And, by constructing the Stuxnet case-based network topology and scenario data, a cyber target importance score is derived with the proposed algorithm, and the cyber target is prioritized to verify the proposed algorithm.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.165-170
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• 2023

There are cases where the mobility impaired have difficulty moving from the moment they leave the house. If guardians also do not have time to entrust their families, who are socially disadvantaged, to a shelter, the guardian has no choice but to check directly in order to know the location of the guardian. The AI home care solution was designed to relieve the anxiety and labor of caregivers and to provide convenience for protection facility officials and users. If more facilities distribute and use services free of charge to non-profit foundations and protective facilities, the concern of guardians will be reduced, and the burden of facility officials who have to manage facility users will be reduced. In this paper, we provide emergency notification services to guardians in the event of an emergency as well as location and status alarms for guardians, which are all data related to movement, in consideration of the mobility vulnerable. Furthermore, it is necessary to provide a service function that recommends the optimal route using a navigation function to ease the convenience and burden of facility officials. It is necessary to alleviate anxiety by providing necessary information to the guardian, such as the location of the shuttle used by the mobile weak and the time of getting on and off. In addition, while providing services for free, the goal is to improve the quality of service for facility managers and the quality of service for the mobility weak.

• Journal of Platform Technology
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• v.11 no.2
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• pp.39-53
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• 2023

Non-installation program (hereinafter referred to as "portable program") is a program that can be used without an installation process, unlike general software. Since there is no separate installation process, portable programs have high mobility and are used in various ways. For example, when initial setup of multiple PCs is required, a portable program can be stored on one USB drive to perform initial setup. Alternatively, when a problem occurs with the PC and it is difficult to boot normally, Windows PE can be configured on the USB drive and portable programs can be stored for PC recovery. And the portable program does not directly affect PC settings, such as changing registry values, and does not leave a trace. This means that the portable program has high security. If a portable program is deleted after using it, it is difficult to analyze behavior in a general way. If a user used a portable program for malicious behavior, analysis in a general way has limitations in collecting evidence. Therefore, portable programs must have a new way of behavioral analysis that is different from ordinary installation software. In this paper, after installing the Windows 10 operating system on a virtual machine, we proceed with the scenario with a portable program of Opera and Notepad++. And we analyze this in various ways such as file analysis of the operating system and memory forensics, collect information such as program execution time and frequency, and conduct specific behavioral analysis of user.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.103-109
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• 2023

In this paper, we propose a smart wall switch based on IEEE 802.11b/g/n standard 2.4GHz band communication. As the 4th industrial era evolves, smart home solution development is actively underway, and application cases for smart wall switches are increasing. Most of the Chinese products that preoccupy the market through price competitiveness use Bluetooth and Zigbee communication switches. However, while ZigBee communication is low power, communication speed is slower than Bluetooth and network configuration through a separate hub is additionally required. The Bluetooth method has problems in that the communication range and speed are lower than Wi-Fi communication, the communication standby time is relatively long, and security is weak. In this study, an IEEE 802.11b/g/n smart wall switch applied with Wi-Fi communication technology was developed. In addition, through the two-wire structure, it is designed so that no additional cost is incurred through the construction of a separate neutral line in the building. The result of the study is more than 30% cheaper than the existing wall switch, so it is judged that it will be able to preoccupy the market not only in terms of technological competitiveness but also price competitiveness.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.