• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.59-73
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• 2021

Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea. This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence. These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.409-416
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• 2020

Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

• Industry Promotion Research
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• v.8 no.1
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• pp.35-45
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• 2023

This paper addressed the analysis of the trend and direction of the US defense strategy based on their third offset strategy and presented the practical policy implication of ensuring the security of South Korea appropriately in the future national defense environment. The countermeasures for the development ability of advanced weapon systems and secure core technologies for Korea were presented in consideration of the US third offset strategy for the future national defense environment. First, to carry out the innovation of national defense in Korea based on artificial intelligence(AI), the long-term basis strategy for the operation of the unmanned robot and autonomous weapon system should be suggested. Second, the platform for AI has to be developed to obtain the development of algorithms and computing abilities for securing the collection/storage/management of national defense data. Lastly, advanced components and core technologies are identified, which the Korean government can join to develop with the US on a basis of the Korea-US alliance, and the technical cooperation with the US should be stronger.

• Convergence Security Journal
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• v.23 no.1
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• pp.147-159
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• 2023

Recently, Chat GPT artificial intelligence (AI) is of keen interest to all governments, companies, and military sectors around the world. In the existing era of literacy AI, it has entered an era in which communication with humans is possible with generative AI that creates words, writings, and pictures. Due to the complexity of the current laws and ordinances issued during the recent national crisis in Korea and the ambiguity of the timing of application of laws and ordinances, the golden time of situational measures was often missed. For these reasons, it was not able to respond properly to every major disaster and military conflict with North Korea. Therefore, the purpose of this study was to revise the National Crisis Management Basic Act, which can act as a national tower in the event of a national crisis, and to promote artificial intelligence governance by linking artificial intelligence technology with the civil, government, military, and police.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4308-4325
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• 2021

The importance and necessity of artificial intelligence, particularly machine learning, has recently been emphasized. In fact, artificial intelligence, such as intelligent surveillance cameras and other security systems, is used to solve various problems or provide convenience, providing solutions to problems that humans traditionally had to manually deal with one at a time. Among them, information security is one of the domains where the use of artificial intelligence is especially needed because the frequency of occurrence and processing capacity of dangerous codes exceeds the capabilities of humans. Therefore, this study intends to examine the definition of artificial intelligence and machine learning, its execution method, process, learning algorithm, and cases of utilization in various domains, particularly the cases and contents of artificial intelligence technology used in the field of information security. Based on this, this study proposes a method to apply machine learning technology to the method of classifying and detecting malware that has rapidly increased in recent years. The proposed methodology converts software programs containing malicious codes into images and creates training data suitable for machine learning by preparing data and augmenting the dataset. The model trained using the images created in this manner is expected to be effective in classifying and detecting malware.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.547-549
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• 2021

In Artificial Intelligence analysis, the process of creating a model and verifying it is a task that requires computational processing time because it is Batch Processing performed with already generated data. We need to model, validate, and predict real-time data, such as stocks and defense information, with data generated directly in front of us. As a solution to this, we solve it by applying techniques to segment the data required for artificial intelligence modeling tasks in order of time processing and distribute the data across multiple processes.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.3
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• pp.1-7
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• 2023

Recently, in the defense field, efforts are being made to collect data by building data centers to incorporate artificial intelligence technology. Weapon system training data can be used as input data for artificial intelligence models and can be used as high-quality data to maximize training performance and develop military strategies. However, training data contains personal information such as the names and military numbers of the personnel who operated the equipment, and training records that reveal the characteristics of the weapon system. If such data is passed on to the enemy, not only the specifications and performance of the weapon system but also the proficiency of each operator may be exposed. In this paper, we propose a pseudonym processing methodology for education and training data security and also suggest a direction for revising related laws.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.375-386
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• 2024

Autonomous weapon systems act according to artificial intelligence-based judgement based on recognition through various sensors. Test and evaluation for various scenarios is required depending on the characteristics that artificial intelligence-based judgement is made. As a part of this approach, this paper proposed a LiDAR point cloud augmentation method for mixed-reality based test and evaluation. The augmentation process is achieved by mixing real and virtual LiDAR signals based on the virtual LiDAR synchronized with the pose of the autonomous weapon system. For realistic augmentation of test and evaluation purposes, appropriate intensity values were inserted when generating a point cloud of a virtual object and its validity was verified. In addition, when mixing the generated point cloud of the virtual object with the real point cloud, the proposed method enhances realism by considering the occlusion phenomenon caused by the insertion of the virtual object.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.