• Journal of Information Technology Services
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• v.15 no.2
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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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• v.18 no.5
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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.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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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

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.225-229
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• 2017

In this paper, various units of industrial disaster safety threats as well as local and national facilities unit real-time detection and prevention refer to the corresponding system goes into disaster management preparedness, prevention, response recovery of phase I systematic ICT skills that can be managed more efficiently. In addition, the immediate disaster prevention and preparedness for early forecasting preemptive damage scale and high-tech information exchange technology to overcome the limitations of a human disaster in the field against the analysis and strategy of preemptive disaster safety management with smart risk management and prevention in response and recovery and the scene quickly and efficient mutual cooperation and effective collaboration and cooperation of the Community Center social security presented a smart disaster safety management system.

• Convergence Security Journal
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• v.18 no.3
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• pp.19-25
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• 2018

Endpoint security is a method of ensuring network security by thoroughly protecting multiple individual devices connected to the network. In this study, we survey the functions and features of various commercial products of endpoint security. Also we emphasizes the importance of endpoint security to respond to the increasingly intelligent and sophisticated security threats against the cloud, mobile, artificial intelligence, and IoT based sur-connection era. and as a way to improve endpoint security, we suggest the ways to improve the life cycle of information security such as preemptive security policy implementation, real-time detection and filtering, detection and modification.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.2
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• pp.130-142
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• 2019

For a preemptive strike against a Time Critical Target(TCT), such as Transporter-Erector-Launcher(TEL), the detection capability of capturing launch signals in the Area of Interest(AoI) is important. In this study, the characteristics of the revisit time and the response time of 6~48 small SAR constellation satellites were analyzed. In particular, the revisit time was analyzed for all regions of North Korea and specific regions, and the response time was classified into [Scenario 1] to identify fixed targets and [Scenario 2] to detect and identify moving targets. In particular, the response time analysis for the TCT detection mission operation in [scenario 2] was performed through optimization analysis of observation cumulative coverage for a specific area. Finally, the configuration of constellation satellites for optimal performance of the detection mission was estimated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.267-280
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• 2023

With development of computing and communications technologies, IoT environments based on high-speed networks have been extending rapidly. Especially, from home to an office or a factory, applications of IoT devices with sensing environment and performing computations are increasing. Unfortunately, IoT devices which have limited hardware resources can be vulnerable to cyber attacks. Hence, there is a concern that an IoT botnet can give rise to information leakage as a national cyber security crisis arising from abuse as a malicious waypoint or propagation through connected networks. In order to response in advance from unknown cyber threats in IoT networks, in this paper, We firstly define four types of We firstly define four types of characteristics by analyzing darknet traffic accessed from an IoT botnet. Using the characteristic, a suspicious IP address is filtered quickly. Secondly, the filtered address is identified by Cyber Threat Intelligence (CTI) or Open Source INTelligence (OSINT) in terms of an unknown suspicious host. The identified IP address is finally fingerprinted to determine whether the IP is a malicious host or not. To verify a validation of the proposed method, we apply to a Darknet on real-world SOC. As a result, about 1,000 hosts who are detected and blocked preemptively by the proposed method are confirmed as real IoT botnets.

• Smart Structures and Systems
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• v.29 no.1
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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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• v.37 no.4
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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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• v.14 no.3
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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.