• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.67-80
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• 1996

Artificial Intelligence(AI) techniques and Object-Oriented(OO) techniques contribute to the simulation modeling of the complex systems. AI techniques are suitable to model human reasoning in the simulation. While OO techniques have advantages of re-usability, maintainability and extendability of the software. Thus, in this paper, we design a knowledge-based object-oriented simulation model, particularly for the logistics analysis of military armor vehicles. The simulation model consists of three modules i.e., scenario, simulation mechanism, and inference engine. The model is designed within the OO paradigm and implemented by using the C++ language. An example case of using the model for the logistic analysis is included.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.637-647
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• 2022

Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.

• Convergence Security Journal
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• v.22 no.5
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• pp.135-143
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• 2022

The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

• Asian Journal of Innovation and Policy
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• v.9 no.1
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• pp.56-78
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• 2020

Changes in our lives due to Artificial Intelligence (AI) are currently ongoing, and there is little refutation of the effectiveness of AI. However, there have been active discussions to minimize the side effects of AI and use it responsibly, and publishing the AI Charter of Ethics (AICE) is one result of it. This study examines how our society is responding to threats from AI that may emerge in the future by examining various AIECs in the Republic of Korea. First, we summarize seven AI threats and classify these into three categories: AI's value judgment, malicious use of AI, and human alienation. Second, from Korea's seven AICEs, we draw fourteen topics based on three categories: protection of social values, AI control, and fostering digital citizenship. Finally, we review them based on the seven AI threats to evaluate any gaps between the threats and our responses. The analysis indicates that Korea has not yet been able to properly respond to the threat of AI's usurpation of human occupations (jobs). In addition, although Korea's AICEs present appropriate responses to lethal AI weapons, these provisions will be difficult to realize because the competition for AI weapons among military powers is intensifying.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.481-486
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• 2023

Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.219-230
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• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.188-196
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• 2023

In the future battlefield centered on the concept of mosaic warfare, the need for an unmanned combat system will increase to value human life. It is necessary for Multiple/Heterogeneous Unmanned Combat Systems to have suitable mission planning method in order to perform various mission. In this paper, we propose the MTSR model for mission planning of the unmanned combat system, and introduce a method of identifying a task by a combination of services using a request operator and a method of allocating resources to perform a task using the requested service. In order to verify the performance of the proposed task-resource matchmaking algorithm, simulation using occupation scenarios is performed and the results are analyzed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.577-589
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• 2023

Ministry of National Defense plans to harness AI as a key technology to bolster overall defense capability for cultivation of an advanced strong military based on science and technology based on Defense Innovation 4.0 Plan. However, security threats due to the characteristics of AI can be a real threat to AI-based defense information system. In order to solve them, systematic security activities must be carried out from the development stage. This paper proposes security activities and considerations that must be carried out at each stage of AI-based defense information system. Through this, It is expected to contribute to preventing security threats caused by the application of AI technology to the defense field and securing the safety and reliability of defense information system.