• Convergence Security Journal
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• v.18 no.2
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• pp.77-88
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• 2018

The purposes of this paper are to research the military utilization of weather modification techniques and to induce their research priority when considering the Korean Peninsular environment and technical level. To achieve these goals, the advantages and disadvantages of weather modification technologies have been discussed, and the evaluation index evaluation was derived through the Delphi method, and the weight of the evaluation index and the final research priority were induced through analytic hierarchical process. Analysis shows that the ionospheric modulation technology has the highest priority in terms of effectiveness as a weapon system and compatibility in the Korean Peninsula environment. It is expected that Korean ionosphere modification can disturb C4ISR function of the enemy and guarantee ours reliably when operating PGM, military satellite, surveillance & reconnaissance equipments, etc. Other weather modification technologies except for ionosphere modification should be developed gradually in that potential threat can be expanded to neighboring countries after the Unification of the Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.613-621
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• 2019

Recently, with the development of the Internet of Things (IoT) and cloud computing technologies, security threats have increased as malicious codes infect IoT devices, and new malware spreads ransomware to cloud servers. In this study, we propose a threat-detection technique that checks obfuscated script patterns to compensate for the shortcomings of conventional signature-based and behavior-based detection methods. Proposed is a malicious code-detection technique that is based on malicious script-pattern analysis that can detect zero-day attacks while maintaining the existing detection rate by registering and checking derived distribution patterns after analyzing the types of malicious scripts distributed through websites. To verify the performance of the proposed technique, a prototype system was developed to collect a total of 390 malicious websites and experiment with 10 major malicious script-distribution patterns derived from analysis. The technique showed an average detection rate of about 86% of all items, while maintaining the existing detection speed based on the detection rule and also detecting zero-day attacks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1052-1057
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• 2020

With the development of new ICT technology, smart keys for vehicles are terminals with ICT technology. Therefore, when the vehicle and the smart key communicate with RF, a cyber hacking attack is possible. Cyber-attacks on smart keys can pose a threat to vehicle theft and vehicle control. Therefore, it is necessary to study hacking attacks and vulnerabilities of smart keys for autonomous vehicles. In this paper, we analyze the cyber attack case of RF communication for vehicles and smart keys. In addition, a real RF cyber attack on the smart key is performed, and the vulnerability of radio wave replication in the same frequency band is found. In this paper, we analyze the vulnerability of RF communication between vehicles and smart keys, and propose a countermeasure against cyber security. In the future, plans to strengthen cyber attacks and security through the popularization of autonomous vehicles will become basic data to protect human and vehicle safety.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.5
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• pp.73-86
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• 2007

Numerous types of models have been developed in recent years in response to the cyber threat posed by worms in order to analyze their propagation and predict their spread. Some of the most important ones involve mathematical modeling techniques such as Epidemic, AAWP (Analytical Active Worm Propagation Modeling) and LAAWP (Local AAWP). However, most models have several inherent limitations. For instance, they target worms that employ random scanning in the entire nv4 network and fail to consider the effects of countermeasures, making it difficult to analyze the extent of damage done by them and the effects of countermeasures in a specific network. This paper extends the equations and parameters of AAWP and LAAWP and suggests ALAAWP (Advanced LAAWP), a new worm simulation technique that rectifies the drawbacks of existing models.

• Convergence Security Journal
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• v.20 no.4
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• pp.35-45
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• 2020

Cyber attacks on the aviation weapon system, a state-of-the-art asset, have become a reality and are approaching as a constant threat. However, due to the characteristics of embedded software of the current aviation weapon system, it is managed and operated without connection to the network in peacetime, so the response management to cyber attacks is relatively weak. Therefore, when a cyber attack becomes a reality, it is urgent to prepare and evaluate measures for the adverse effects that such attack will have on the execution of the Air Tasking Order(ATO). In this paper, we propose a framework for operational impact assessment in order to avoid confusion in ATO execution and systematic response to cyber attacks on aviation weapons systems. The proposed framework is designed to minimize the negative impact on operations against cyber attacks that may occur under no warning by analyzing the impact on air operations for each aviation weapon system and standardizing countermeasures for this. In addition, it supports the operational commander to make a quick decision to command for the execution of the operation even in a situation where a cyber attack occurs.

• Convergence Security Journal
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• v.20 no.4
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• pp.71-80
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• 2020

In order to provide realistic traffic to the cyber warfare training system, it is necessary to prepare a traffic distribution plan in advance and to create a training data set using normal/threat data sets. This paper presents the design and implementation results of a method for creating a traffic distribution plan and a training data set to provide background traffic like a real environment to a cyber warfare training system. We propose a method of a traffic distribution plan by using the network topology of the training environment to distribute traffic and the traffic attribute information collected in real and simulated environments. We propose a method of generating a training data set according to a traffic distribution plan using a unit traffic and a mixed traffic method using the ratio of the protocol. Using the implemented tool, a traffic distribution plan was created, and the training data set creation result according to the distribution plan was confirmed.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.73-82
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• 2022

Marine fisheries resources face major anthropogenic threat from unregulated fishing activities; thus require precise detection for protection through marine surveillance. Korea developed an efficient land-based small fishing vessel monitoring system using real-time V-Pass data. However, those data directly do not provide information on fishing activities, thus further efforts are necessary to differentiate their activity status. In Korea, especially in Busan, longlining is practiced by many small fishing vessels to catch several types of fishes that need to be identified for proper monitoring. Therefore, in this study we have improved the existing fishing status classification method by applying Hidden Markov Model (HMM) on V-Pass data in order to further classify their fishing status into three groups, viz. non-fishing, longlining and other types of fishing. Data from 206 fishing vessels at Busan on 05 February, 2021 were used for this purpose. Two tiered HMM was applied that first differentiates non-fishing status from the fishing status, and finally classifies that fishing status into longlining and other types of fishing. Data from 193 and 13 ships were used as training and test datasets, respectively. Using this model 90.45% accuracy in classifying into fishing and non-fishing status and 88.23% overall accuracy in classifying all into three types of fishing statuses were achieved. Thus, this method is recommended for monitoring the activities of small fishing vessels equipped with V-Pass, especially for detecting longlining.

• Maritime Security
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• v.3 no.1
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• pp.1-44
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• 2021

China's new Maritime Policy Law (MPL) purports to regulate the duties of China's maritime police agencies, including the China Coast Guard, and safeguard China's sovereignty, security, and rights and interest. The MPL has potentially far-reaching application, as China claims extensive maritime areas off its mainland and in the South China Sea. This expansive application of maritime law enforcement jurisdiction is problematic given that most of China's maritime claims are inconsistent with international law. To the extent that the MPL purports to assert jurisdiction over foreign flagged vessels in disputed areas or on the high seas, it contravenes international law. Numerous provisions of the MPL regarding the use of force are also inconsistent with international rules and standards governing the use of maritime law enforcement jurisdiction, as well as the UN Charter's prohibition on the threat or use of force against the territorial integrity or political independence of any state. China could use the MPL as a subterfuge to advance its illegal territorial and maritime claims in the South and East China Seas and interfere with coastal State resource rights in their respective exclusive economic zone.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.195-207
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• 2022

COVID-19 has remained one of the most serious health crises in recent history, resulting in the tragic loss of lives and significant economic impacts on the entire world. The difficulty of controlling COVID-19 poses a threat to the global health sector. Considering that Artificial Intelligence (AI) has contributed to improving research methods and solving problems facing diverse fields of study, AI algorithms have also proven effective in disease detection and early diagnosis. Specifically, acoustic features offer a promising prospect for the early detection of respiratory diseases. Motivated by these observations, this study conceptualized a speech-based diagnostic model to aid in COVID-19 diagnosis. The proposed methodology uses speech signals from confirmed positive and negative cases of COVID-19 to extract features through the pre-trained Visual Geometry Group (VGG-16) model based on Mel spectrogram images. This is used in addition to the K-means algorithm that determines effective features, followed by a Genetic Algorithm-Support Vector Machine (GA-SVM) classifier to classify cases. The experimental findings indicate the proposed methodology's capability to classify COVID-19 and NOT COVID-19 of varying ages and speaking different languages, as demonstrated in the simulations. The proposed methodology depends on deep features, followed by the dimension reduction technique for features to detect COVID-19. As a result, it produces better and more consistent performance than handcrafted features used in previous studies.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.57-66
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• 2023

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.