• 한국IT서비스학회지
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• 제15권2호
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• pp.157-167
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• 2016

Task environment for enterprises and public institutions are moving into cyberspace-based environment and structing the LTE wireless network. The applications "App" operated in the LTE wireless network are mostly being developed with Android-based. But Android-based malwares are surging and they are the potential DDoS attacks. DDoS attack is a major information security threat and a means of cyber attacks. DDoS attacks are difficult to detect in advance and to defense effectively. To this end, a DMZ is set up in front of a network infrastructure and a particular server for defensive information security. Because There is the proliferation of mobile devices and apps, and the activation of android diversify DDoS attack methods. a DMZ is a limit to detect and to protect against DDoS attacks. This paper proposes an information security method to detect and Protect DDoS attacks from the terminal phase using a Preemptive military strategy concept. and then DDoS attack detection and protection app is implemented and proved its effectiveness by reducing web service request and memory usage. DDoS attack detection and protecting will ensure the efficiency of the mobile network resources. This method is necessary for a continuous usage of a wireless network environment for the national security and disaster control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1301-1316
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• 2024

In modern warfare, missiles play a pivotal role but typically spend the majority of their lifecycle in long-term storage or standby mode, making it difficult to detect failures. Preemptive detection of missiles that will fail is crucial to preventing severe consequences, including safety hazards and mission failures. This study proposes a contamination-based stacking ensemble model, employing the local outlier factor (LOF), to detect such missiles. The proposed model creates multiple base LOF models with different contamination values and combines their anomaly scores to achieve a robust anomaly detection. A comparative performance analysis was conducted between the proposed model and the traditional single LOF model, using production-related inspection data from missiles deployed in the military. The experimental results showed that, with the contamination parameter set to 0.1, the proposed model exhibited an increase of approximately 22 percentage points in accuracy and 71 percentage points in F1-score compared to the single LOF model. This approach enables the preemptive identification of potential failures, undetectable through traditional statistical quality control methods. Consequently, it contributes to lower missile failure rates in real battlefield scenarios, leading to significant time and cost savings in the military industry.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.707-713
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• 2021

Symptoms of foot-and-mouth disease include fever and drooling a lot around the hoof, blisters in the mouth, poor appetite, blisters around the hoof, and blisters around the hoof. Research is underway on smart barns that remotely manage these symptoms through cameras. Visible light cameras can measure the condition of livestock such as blisters, but cannot measure body temperature. On the other hand, infrared thermal imaging cameras can measure body temperature, but it is difficult to measure the condition of livestock. In this paper, we propose an object detection system using deep learning-based livestock detection using visible and infrared thermal imaging composite camera modules for preemptive response

• 디지털콘텐츠학회 논문지
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• 제18권1호
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• pp.225-229
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• 2017

본 논문에서는 다양한 재난안전 위협요소를 단위 산업체 시설물뿐만 아니라 지역 및 국가 단위에서 실시간으로 감지 예측하고 예방 대응하는 시스템에 대하여 알아본다. 예방 대비 대응 복구로 이뤄지는 재난관리의 전 단계를 체계적 효율적으로 관리할 수 있는 정보통신기술을 기반으로한 융복합 구현에 대하여 분석하였다. 또한 조기예측을 통한 선제적 예방과 대비 즉각적인 재난 정보 전달로 피해규모의 축소와 첨단 기술을 통해 재난현장에서의 인간한계 극복에 대하여 분석하였으며 스마트 재난안전관리의 전략으로 선제적 위험관리 및 예방 신속하고 효율적 현장 대응 및 복구와 민관 상호협력 및 효율적 연계협력의 사회안전 스마트 재난안전관리 시스템을 제시하였다.

• 융합보안논문지
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• 제18권3호
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• pp.19-25
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• 2018

엔드포인트 보안은 네트워크에 연결된 여러 개별 장치를 철저하게 보호함으로써 네트워크 보안을 보장하는 방법입니다. 본 연구에서는 엔드포인트 보안의 다양한 상용제품의 기능과 특 장점을 살펴본다. 그리고 클라우드, 모바일, 인공지능, 그리고 사물인터넷 기반의 초연결시대를 대비하여 날로 지능화되고 고도화되는 보안위협에 대응하기 위한 엔드포인트 보안의 중요성을 강조하고, 그 개선방안으로서 선제적인 보안 정책 구현, 실시간 탐지 및 필터링, 탐지 및 수정 등의 정보보안의 생명주기의 개선방안을 제시한다.

• 한국항공우주학회지
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• 제47권2호
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• pp.130-142
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• 2019

이동식미사일발사대(TEL)와 같은 시한성 긴급표적(TCT)에 대한 선제타격을 위해서는 관심지역(AoI)에서의 발사징후를 포착하는 탐지성능이 중요하다. 탐지성능의 극대화를 위해서는 재방문주기 및 시스템응답주기의 최소화를 위해 가능한 한 다수의 군집위성 전개가 필요하다. 본 연구에서는 6~48기의 소형 SAR 군집위성 전개 시 재방문주기와 응답주기의 특성을 분석하였다. 재방문주기는 북한의 전지역 및 특정지역에 대해 분석하였으며, 응답주기는 고정표적을 식별하는 [시나리오 1]과 이동표적을 탐지 및 식별하는 [시나리오 2]로 분류하여 분석을 수행하였다. 특히, [시나리오 2]의 TCT 탐지임무 운용에 대한 응답주기 분석은 특정 면적에 대한 관측 누적 커버리지의 최적화 분석을 통해 수행하였다. 그리고 탐지임무의 최적 성능을 위한 군집궤도 형상을 분석하였다.

• 정보보호학회논문지
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• 제33권2호
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• pp.267-280
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• 2023

최근 컴퓨팅 및 통신 기술의 발달로 인해 IoT 디바이스가 급격히 확산·보급되고 있다. 특히 IoT 디바이스는 가정에서부터 공장에 이르기까지 그 목적에 따라 연산을 수행하거나 주변 환경을 센싱하는 등의 기능을 보유하고 있어 실생활에서의 활용이 폭넓게 증가하고 있다. 하지만, 제한된 수준의 하드웨어 자원을 보유한 IoT 디바이스는 사이버공격에 노출되는 위험도가 높으며, 이로 인해 IoT 봇넷은 악성행위의 경유지로 악용되거나 연결된 네트워크로 감염을 빠르게 확산함으로써 단순한 정보 유출뿐만 아니라 범국가적 위기를 초래할 가능성이 존재한다. 본 논문에서는 폭넓게 활용되고 있는 IoT 네트워크에서 알려지지 않은 보안위협에 선제적으로 대응하기 위해 IoT 봇넷의 네트워크 행위특징을 활용한 선제탐지 방법을 제안한다. IoT 봇넷이 접근하는 다크넷 트래픽을 분석하여 4가지 행위특징을 정의하고 이를 통해 감염의심 IP를 빠르게 선별한다. 분류된 IP는 사이버 위협 인텔리전스(CTI)를 활용하여 알려지지 않은 의심 호스트 여부를 확인한 후, 디바이스 핑거프린팅을 통해 IoT 봇넷에의 소속 여부를 최종 결정한다. 제안된 선제탐지 방법의 유효성 검증을 위해 실제 운용 중인 보안관제 환경의 다크넷 대역에 방법론 적용 및 확인 결과, 선제탐지 한 약 1,000개의 호스트가 실제 악성 IoT 봇넷임을 10개월간 추적관찰로 검증하여 그 유효성을 확인하였다.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Kidney Research and Clinical Practice
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• 제37권4호
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• pp.323-337
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• 2018

Infectious complications have been considered as a major cause of morbidity and mortality after kidney transplantation, especially in the Asian population. Therefore, prevention, early detection, and prompt treatment of such infections are crucial in kidney transplant recipients. Among all infectious complications, viruses are considered to be the most common agents because of their abundance, infectivity, and latency ability. Herpes simplex virus, varicella zoster virus, Epstein-Barr virus, cytomegalovirus, hepatitis B virus, BK polyomavirus, and adenovirus are well-known etiologic agents of viral infections in kidney transplant patients worldwide because of their wide range of distribution. As DNA viruses, they are able to reactivate after affected patients receive immunosuppressive agents. These DNA viruses can cause systemic diseases or allograft dysfunction, especially in the first six months after transplantation. Pretransplant evaluation and immunization as well as appropriate prophylaxis and preemptive approaches after transplant have been established in the guidelines and are used effectively to reduce the incidence of these viral infections. This review will describe the etiology, diagnosis, prevention, and treatment of viral infections that commonly affect kidney transplant recipients.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.101-107
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• 2022

In Korea, the military has been conducting counseling forthe preemptive detection of psychologically unstable soldiers to prevent unexpected accidents and to help them adapt to military life. However, several soldiers feel anxious about face-to-face counseling with military officers and they have difficulty expressing themselves. Video See-Through HMD is a state-of-the-art mixed reality device that converts the user's real view into a digital view, which leads users to feel the actual situation as the virtual. To validate its usefulness as a new psychological counseling aid, we investigated 11 army soldiers who are under the counseling program in barracks. During the counseling conversation, participants were asked to wear or take off the Video See-Through HMD repeatedly. All conversations were recorded for behavioral observation. As a result, 80% of the soldiers showed a relatively stable state of mind when wearing the Video See-Through HMD, which leads them to be innocent and frank about their concerns. This method could improve the effectiveness of counseling to prevent unexpected accidents caused by unnoticeable psychological instabilities of the clients.