• 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 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.352-360
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• 2023

Recently, AI pilots using reinforcement learning are developing to a level that is more flexible than rule-based methods and can replace human pilots. In this paper, a curriculum was used to help head-on combat with reinforcement learning. It is not easy to learn head-on with a reinforcement learning method without a curriculum, but in this paper, through the two circle-based head-on air combat learning technique, ownship gradually increase the difficulty and become good at head-on combat. On the two-circle, the ATA angle between the ownship and target gradually increased and the AA angle gradually decreased while learning was conducted. By performing reinforcement learning with and w/o curriculum, it was engaged with the rule-based model. And as the win ratio of the curriculum based model increased to close to 100 %, it was confirmed that the performance was superior.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.135-144
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• 2023

Artificial Intelligence (AI) is a prominent topic in almost every field. In Korea, Systems Engineering (SE) procedures are applied in Defense Acquisition, and it is anticipated that SE procedures will also be applied to systems incorporating AI capabilities. This study explores the applicability of the concepts "AI4SE (AI for SE)" and "SE4AI (SE for AI)," which have been proposed in the United States, to the Korean context. The research examines the feasibility of applying these concepts, identifies necessary tasks, and proposes implementation strategies. For the AI4SE, many attempts and studies applying AI to SE Processes both Requirements & Architectures Define, System implementation & V&V, and Sustainment. It needs Explainability and Security. For the SE4AI, the Functional AI implementation level, Quality & Security of the Data-set, AI Ethics, and Review policies are needed. Furthermore, it provides perspectives on how these two concepts should ultimately converge and suggests future directions for development.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.