• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.527-536
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• 2024

In the digital age, the growth of AI and digital technologies brings opportunities and cybersecurity risks. At the forefront of this change are teenagers, referred to as 'digital natives'. However, they may have difficulty using technology safely without proper information security knowledge. This paper highlights the need for information security education for teenagers in South Korea by referring to cases in the UK, Australia, and the US. These countries are already providing education that prepares young people for cyber threats and future societal needs. Reflecting this trend, South Korea should also establish comprehensive information security education for teenagers to equip them for the digital age.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.333-336
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• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.25-25
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• 2023

빅데이터, AI, 인공지능 등 기술이 발전함에 있어서 자율운항도입에 따른 VTS 체계변화에 대한 인식이 필요한 실정이다. 이 연구에서는 자율운항선박이 상용화함에 따라 요구되는 적합성을 제고하기 위해 영향을 미치는 내외적인 환경요인들을 전문가집단의 브레인스토밍, 설문조사, 인터뷰 등 다방면으로 조사하고, 해당 요소를 기반으로 TOWS분석을 통해 강점(Strength), 약점(Weakness), 기회(Opportunities), 위협(Threats)의 각 요소를 상호 결합해 전략주제 도출 및 새로운 관제절차와 관련 기술, 자율운항 교육프로그램, 사이버 보안조치, 자율운항 관련 알고리즘 구성 요소 등 구체적 실행계획을 제시함으로써 예측되는 변화 대응에 기여하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.209-214
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• 2023

In the future, as autonomous vehicles become popular at home and abroad, the frequency of accidents involving autonomous vehicles is also expected to increase. In particular, when a fully autonomous vehicle is operated, various criminal/civil problems such as sexual violence, assault, and fraud between passengers may occur as well as the vehicle accident itself. In this case, forensics for accidents involving autonomous vehicles and accidents involving passengers in the vehicles are also about to change. This paper reviewed the types of security threats of autonomous vehicles, methods for maintaining the integrity of evidence data using blockchain technology, and research on digital forensics. Through this, it was possible to describe threats that would occur in autonomous vehicles using blockchain technology and forensic techniques for each type of accident in a scenario-type manner. Through this study, a block that helps forensics of self-driving vehicles before and after accidents by investigating forensic security technology of domestic and foreign websites to respond to vulnerabilities and attacks of autonomous vehicles, and research on block chain security of research institutes and information security companies. A chain method was proposed.

• Convergence Security Journal
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• v.23 no.5
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• pp.65-72
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• 2023

This paper proposes a method for detecting malicious domains considering human habitual characteristics by building a Deep Learning model based on LSTM (Long Short-Term Memory). DGA (Domain Generation Algorithm) malicious domains exploit human habitual errors, resulting in severe security threats. The objective is to swiftly and accurately respond to changes in malicious domains and their evasion techniques through typosquatting to minimize security threats. The LSTM-based Deep Learning model automatically analyzes and categorizes generated domains as malicious or benign based on malware-specific features. As a result of evaluating the model's performance based on ROC curve and AUC accuracy, it demonstrated 99.21% superior detection accuracy. Not only can this model detect malicious domains in real-time, but it also holds potential applications across various cyber security domains. This paper proposes and explores a novel approach aimed at safeguarding users and fostering a secure cyber environment against cyber attacks.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.1-9
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• 2021

The core competencies such as technology have been rapidly developing with advent of the fourth industrial revolution. One of the representative technologies in the era of the 4th Industrial Revolution is artificial intelligence(AI). In particular, AI makes human life richer and more comfortable and has many positive aspects. The negative aspect is that AI is likely to replace the organizational members' job and has the ability to replace skills associated with it. These threats may increase the level of perception that organizational members may loss their job. Moreover, it may lead to a sense of anxiety. In addition, organizational members who perceive job uncertainty highly, the job substitution anxiety may be become highly. According to this, their job satisfaction can be lower. Overall, this research emphasized the negative aspects of AI in contrast to the positive aspects of the fourth industrial era. It is also emphasized that the organization should need to recognize such problems and seek solutions to reduce workers' anxiety. Finally, practical implications and research directions of future study were presented through the research results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.891-898
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• 2022

Along with global interest, drones are expanding the base of utilization such as transportation of goods, forest protection, and safety management, and cluster flights are being applied in various fields such as military operations and environmental monitoring. Currently, specialized networks such as e-UM 5G for services in specific industries are being established in Korea. In this regard, drone systems are also moving to establish specialized networks to provide services that are fused with AI and autonomous flight. As drones converge with various services, various security threats in various environments are also subordinated, and in response, requirements and guidelines for drone security are being prepared in Korea. In this paper, we propose a technology method for peer identification and safe information provision between cluster flight drones by utilizing a cryptographic module equipped with wireless LAN and quantum entropy-based random number generator in a cluster flight system and a mobile communication network such as e-UM 5G.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.691-708
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• 2022

As the technology of machine learning and deep learning became common, it began to be applied to research on anomaly(abnormal) detection of industrial control systems. In Korea, the HAI dataset was developed and published to activate artificial intelligence research for abnormal detection of industrial control systems, and an AI contest for detecting industrial control system security threats is being conducted. Most of the anomaly detection studies have been to create a learning model with improved performance through the ensemble model method, which is applied either by modifying the existing deep learning algorithm or by applying it together with other algorithms. In this study, a study was conducted to improve the performance of anomaly detection with a post-processing method that detects abnormal data and corrects the labeling results, rather than the learning algorithm and data pre-processing process. Results It was confirmed that the results were improved by about 10% or more compared to the anomaly detection performance of the existing model.

• Convergence Security Journal
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• v.23 no.1
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• pp.109-115
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• 2023

The future outlook for defense faces various and challenging environments such as the acceleration of uncertainty in the global security landscape and limitations in domestic social and economic conditions. In response, the Ministry of National Defense seeks to address the problems and threats through defense innovation based on scientific and technological advancements such as artificial intelligence, drones, and robots. To introduce advanced AI-based technology, it is essential to integrate and utilize data on IT environments such as cloud and 5G. However, existing traditional security policies face difficulties in data sharing and utilization due to mainly system-oriented security policies and uniform security measures. This study proposes a paradigm shift to a data value-based security policy based on theoretical background on data valuation and life-cycle management. Through this, it is expected to facilitate the implementation of scientific and technological innovations for national defense based on data-based task activation and new technology introduction.

• Convergence Security Journal
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• v.22 no.2
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• pp.67-75
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• 2022

Due to the COVID-19 pandemic, many companies have introduced remote work. However, the introduction of remote work has increased attacks on companies to access sensitive information, and many companies have begun to use cloud services to respond to security threats. This study used LDA topic modeling techniques by collecting news data with the keyword 'cloud security' to analyze changes in domestic cloud security trends before and after the COVID-19 pandemic. Before the COVID-19 pandemic, interest in domestic cloud security was low, so representation or association could not be found in the extracted topics. However, it was analyzed that the introduction of cloud is necessary for high computing performance for AI, IoT, and blockchain, which are IT technologies that are currently being studied. On the other hand, looking at topics extracted after the COVID-19 pandemic, it was confirmed that interest in the cloud increased in Korea, and accordingly, interest in cloud security improved. Therefore, security measures should be established to prepare for the ever-increasing usage of cloud services.