• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.49-59
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• 2019

Generative adversarial networks(GANs) have received great attention in the machine learning field for their capacity to model high-dimensional and complex data distribution implicitly and generate new data samples from the model distribution. This paper investigates the model training methodology, architecture, and various applications of generative adversarial networks. Experimental evaluation is also conducted for generating synthetic image dataset for defense using two types of GANs. The first one is for military image generation utilizing the deep convolutional generative adversarial networks(DCGAN). The other is for visible-to-infrared image translation utilizing the cycle-consistent generative adversarial networks(CycleGAN). Each model can yield a great diversity of high-fidelity synthetic images compared to training ones. This result opens up the possibility of using inexpensive synthetic images for training neural networks while avoiding the enormous expense of collecting large amounts of hand-annotated real dataset.

• Structural Engineering and Mechanics
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• v.87 no.4
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• pp.297-304
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• 2023

Targeted introduction of explosion-resisting and energy-absorbing materials and optimization of explosion-resisting composite structural styles in underground engineering are the most important measures for modern engineering protection. They could also improve the survivability of underground engineering in wartime. In order to test explosion-resisting and energy-absorbing effects of high-performance equal-sized-aggregate (HPESA) concrete, the explosive loading tests were conducted on HPESA concrete composite plates by field simple explosion craters. Time-history curves of the explosion pressure at the interfaces were obtained under six conditions with different explosion ranges and different thicknesses of the HPESA concrete plate. Test results show that under the same explosion range, composite plate structures with different thicknesses of the HPESA concrete plate differ significantly in terms of the wave-absorbing ability. Under the three thicknesses in the tests, the wave-absorbing ability is enhanced with the growing thickness and the maximum pressure attenuation index reaches 83.4%. The energy attenuation coefficient of the HPESA concrete plate under different conditions was regressively fitted. The natural logarithm relations between the interlayer plate thickness and the energy attenuation coefficient under the two explosion ranges were attained.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.362-365
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• 2015

DDoS 공격의 빈도와 규모가 계속 증가하고 있으며 그에 따른 피해와 파급도 커지고 있다. 최근 동향에서 봇넷을 이용한 패킷 플루딩 공격이 여전히 상위 공격순위를 차지하고 있다. 공격유형으로는 TCP SYN, UDP fragment 및 SSDP 플루딩 공격 등이 여전히 강세를 보이고 있다. 이러한 공격들은 source IP가 변조된 악의적인 패킷을 대량으로 발생시켜서 공격대상 네트워크 인프라를 마비시킨다. DDoS 공격 탐지를 위해서는 내부로 유입되는 초당 패킷수와 사용자와 서버간의 연결이 네트워크 플로우수의 변화를 관측하는 것이 필요하며 방어를 위해 트래픽 제어 기술이 필요하다. 이에 본 논문에서는 네트워크 서비스 분석 및 제어 기술인 DPI/QoS 솔루션을 이용한 플로우 기반의 DDoS 탐지 및 방어 시스템을 제안한다. 네트워크 모니터링과 제어를 위하여 사용하던 DPI/QoS 솔루션에 DDoS 탐지 및 방어기능을 추가함으로써 효율성 및 경제성에서 강점을 가질 것으로 기대한다.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.145-156
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• 2023

Trajectory of ballistic missile is defined by inherent flight dynamics, which decided range and maneuvering characteristics. It is crucial to predict range and maneuvering characteristics of ballistic missile in KAMD (Korea Air and Missile Defense) to minimize damage due to ballistic missile attacks, Nowadays, needs for applying AI(Artificial Intelligence) technologies are increasing due to rapid developments of DNN(Deep Neural Networks) technologies. To apply these DNN technologies amount of data are required for superviesed learning, but trajectory data of ballistic missiles is limited because of security issues. Trajectory data could be considered as multivariate time series including many variables. And augmentation in time series data is a developing area of research. In this paper, we tried to augment trajectory data of ballistic missiles using recently developed methods. We used TimeVAE(Time Variational AutoEncoder) method and TimeGAN(Time Generative Adversarial Networks) to synthesize missile trajectory data. We also compare the results of two methods and analyse for future works.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4224-4243
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• 2021

Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.