• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.35-47
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• 2022

Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.23-34
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• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.913-926
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• 2022

As information is recognized as a core competency of organizations, organizations are increasingly investing in policies and technologies for information security(IS). Recently, as information exposure accidents by people have occurred continuously, interest in IS behaviors of organization insiders is increasing. This study aims to confirm the effect of the IS environment and support structure established by the organization on the intention of individuals to comply with IS. We conducted a survey of employees in organizations with IS policies and tested the hypothesis using the structural equation of AMOS 22.0 and Process 3.1 using 421 samples. As a result of the analysis, authentic leadership and justice climate, which are factors that build an IS environment, and communication and feedback, which are factors supporting IS compliance, have a positive effect on employees' compliance intention. In addition, authentic leadership, punishment, communication, and feedback were found to reinforce the positive impact of IS justice climate. As the study suggested the overall structural design direction to be pursued to reinforce insider's IS behavior, and the results help to achieve the IS goal.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.94-101
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• 2021

According to the Facility Management System (FMS) operated by the Korea Authority of Land & Infrastructure Safety, it is expected that the number of aging facilities that have been in use for more than 30 years will increase rapidly to 13.9% in 2019 and 34.5% in 2929, and end up with a social problem. In addition, with the revision of "Common Application of Seismic Design Criteria" by the Ministry of Public Administration and Security in 2017, it is mandatory to re-evaluate all existing road facilities and if necessary seismic reinforcement should be done to minimize the magnitude of earthquake damage and perform normal road functions. The seismic performance management-decision support technology currently used in seismic performance management practice in Korea only determines the earthquake-resistance reinforcement priority based on the qualitative index value for the seismic performance of individual facilities. However with this practice, normal traffic functions cannot be guaranteed. A new seismic performance management decision support technology that can provide various judgment data required for decision making is needed to overcome these shortcomings and better perform seismic performance management from a road network perspective.

• 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.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.1-13
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• 2022

As the information and communication environment develops, the environment of military facilities is also development remarkably. In proportion to this, cyber threats are also increasing, and in particular, APT attacks, which are difficult to prevent with existing signature-based cyber defense systems, are frequently targeting military and national infrastructure. It is important to identify attack groups for appropriate response, but it is very difficult to identify them due to the nature of cyber attacks conducted in secret using methods such as anti-forensics. In the past, after an attack was detected, a security expert had to perform high-level analysis for a long time based on the large amount of evidence collected to get a clue about the attack group. To solve this problem, in this paper, we proposed an automation technique that can classify an attack group within a short time after detection. In case of APT attacks, compared to general cyber attacks, the number of attacks is small, there is not much known data, and it is designed to bypass signature-based cyber defense techniques. As an attack model, we used MITRE ATT&CK® which modeled many parts of cyber attacks. We design an impact score considering the versatility of the attack techniques and proposed a group similarity score based on this. Experimental results show that the proposed method classified the attack group with a 72.62% probability based on Top-5 accuracy.

• 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.