• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.605-610
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• 2020

Software Defined Networking (SDN) is setting the standard for the management of networks due to its scalability, flexibility and functionality to program the network. The Distributed Denial of Service (DDoS) attack is most widely used to attack the SDN controller to bring down the network. Different methodologies have been utilized to detect DDoS attack previously. In this paper, first the dataset is obtained by Kaggle with 84 features, and then according to the rank, the 20 highest rank features are selected using Permutation Importance Algorithm. Then, the datasets are trained and tested with Convolution Neural Network (CNN) classifier model by utilizing deep learning techniques. Our proposed solution has achieved the best results, which will allow the critical systems which need more security to adopt and take full advantage of the SDN paradigm without compromising their security.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1595-1603
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• 2020

Online defamation incidents such as Internet news comments on portal sites, SNS, and community sites are increasing in recent years. Bias and hate expressions threaten online service users in various forms, such as invasion of privacy and personal attacks, and defamation issues. In the past few years, academia and industry have been approaching in various ways to solve this problem The purpose of this study is to build a dataset and experiment with deep learning classification modeling for detecting various bias expressions as well as hate expressions. The dataset was annotated 7 labels that 10 personnel cross-checked. In this study, each of the 7 classes in a dataset of about 137,111 Korean internet news comments is binary classified and analyzed through deep learning techniques. The Proposed technique used in this study is multi-channel CNN model with attention. As a result of the experiment, the weighted average f1 score was 70.32% of performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.691-705
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• 2012

Buffer overflow vulnerability is the most representative one that an attack method and its countermeasure is frequently developed and changed. This vulnerability is still one of the most critical threat since it was firstly introduced in middle of 1990s. Shellcode is a machine code which can be used in buffer overflow attack. Attackers make the shellcode for their own purposes and insert it into target host's memory space, then manipulate EIP(Extended Instruction Pointer) to intercept control flow of the target host system. Therefore, a lot of research to defend have been studied, and attackers also have done many research to bypass security measures designed for the shellcode defense. In this paper, we investigate shellcode defense and attack techniques briefly and we propose our new methodology which can hide shellcode in the 24bit BMP image. With this proposed technique, we can easily hide any shellcode executable and we can bypass the current detection and prevention techniques.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.213-218
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• 2021

In this paper, we detect and track vehicles by type based on highway daytime driving videos taken with black boxes for vehicles. In addition, we design a real-time MR contents production method that can be newly created by placing substitute videos of each type of detected vehicles in the same location as the new background video. To detect and track vehicles by type, we use the YOLO algorithm. And we also use the mask technique based on RGB color for substitute videos of each type of vehicles detected. The size of the vehicle substitute videos to be used for MR content are substituted by the same size as the area size of the detected vehicles. In this paper, we confirm that real-time MR contents design is possible as a result of experiments and simulations and believe that It will be usefully utilized in the field of VR contents.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.100-106
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• 2021

Measuring Intima-media thickness (IMT) with ultrasound images can help early detection of coronary artery disease. As a result, numerous machine learning studies have been conducted to measure IMT. However, most of these studies require several steps of pre-treatment to extract the boundary, and some require manual intervention, so they are not suitable for on-site treatment in urgent situations. in this paper, we propose to use deep learning networks U-Net, Attention U-Net, and Pretrained U-Net to automatically segment the intima-media complex. This study also applied the HE, HS, and CLAHE preprocessing technique to wireless portable ultrasound diagnostic device images. As a result, The average dice coefficient of HE applied Models is 71% and CLAHE applied Models is 70%, while the HS applied Models have improved as 72% dice coefficient. Among them, Pretrained U-Net showed the highest performance with an average of 74%. When comparing this with the mean value of IMT measured by Conventional wired ultrasound equipment, the highest correlation coefficient value was shown in the HS applied pretrained U-Net.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.127-134
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• 2020

Recently, Harmful sites, including pornographic videos, drugs, personal information and hacking tool distribution sites, have caused serious social problems. However, due to the nature of the Internet environment where anyone can use it freely, it is difficult to control the user effectively. And the site operator operates by changing the domain to bypass the blockage. Therefore, even once identified sites have low persistence. In this paper, we propose multi-channel domain tracking technology, a technique that can effectively track changes in the domain addresses of harmful sites, including the same or similar content, by tracking changes in these harmful sites. Proposed technology is a technology that can continuously track information in a domain using OSINT technology. We tested and verified that the proposed technology was effective for domain tracking with a 90.4% trace rate (sensing 66 changes out of 73 domains).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.576-583
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• 2020

This paper proposes a technique to determine the spam comments on YouTube, which have recently seen tremendous growth. On YouTube, the spammers appeared to promote their channels or videos in popular videos or leave comments unrelated to the video, as it is possible to monetize through advertising. YouTube is running and operating its own spam blocking system, but still has failed to block them properly and efficiently. Therefore, we examined related studies on YouTube spam comment screening and conducted classification experiments with six different machine learning techniques (Decision tree, Logistic regression, Bernoulli Naive Bayes, Random Forest, Support vector machine with linear kernel, Support vector machine with Gaussian kernel) and ensemble model combining these techniques in the comment data from popular music videos - Psy, Katy Perry, LMFAO, Eminem and Shakira.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.25-30
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• 2021

In this paper, we studied the coding technique for flicker mitigation and BER performance improvement in visible light communication system. In order to increase the transmission speed of visible light communication, a multi-transmission multi-LED transmission system using a plurality of LEDs is being actively studied. However, when data is transmitted through N LEDs in a multi-LED visible light communication system using N LEDs, there is a continuous zero section in which 0 is transmitted simultaneously according to the data sequence, and since the transmission section of 1 is different, flickering Or, a phenomenon in which the dimming level changes occurs. The visible light communication system is a communication system that simultaneously performs communication and lighting functions. Therefore, transmission efficiency of communication and brightness of lighting must be considered at the same time. To solve this problem, we proposed a flicker reduction mapping that can alleviate flicker and dimming level problems, improve error detection and BER performance through coding mapping of each LED data sequence.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1081-1088
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• 2020

In this paper, the method of detecting sea fog through CCTV image is proposed based on convolutional neural networks. The study data randomly extracted 1,0004 images, sea-fog and not sea-fog, from a total of 11 ports or beaches (Busan Port, Busan New Port, Pyeongtaek Port, Incheon Port, Gunsan Port, Daesan Port, Mokpo Port, Yeosu Gwangyang Port, Ulsan Port, Pohang Port, and Haeundae Beach) based on 1km of visibility. 80% of the total 1,0004 datasets were extracted and used for learning the convolutional neural network model. The model has 16 convolutional layers and 3 fully connected layers, and a convolutional neural network that performs Softmax classification in the last fully connected layer is used. Model accuracy evaluation was performed using the remaining 20%, and the accuracy evaluation result showed a classification accuracy of about 96%.

• Pediatric Infection and Vaccine
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• v.28 no.2
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• pp.118-123
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• 2021

Culture tests are very important in choosing the appropriate antibiotics for bacterial infections. In some cases, bacteria that could not be identified in standard culture bottles could be detected using blood culture bottles. A previously healthy 13-year-old boy visited our emergency room. He experienced pain, redness, and hardness of periumbilical skin and a fever for five days. There was no history of abdominal surgery and penetrating trauma. Computed tomography showed abscess with cellulitis at the periumbilical soft tissue with no congenital anomaly. Ultrasonography-guided aspiration was performed, and about 8.5 mL of the purulent abscess was aspirated. The abscess was cultured using blood culture bottle. The pus grew Actinomyces radingae and Clostridium ramosum. When performing the pus culture, using blood culture bottles can be more effective and rapid than the standard culture method for the detection of bacterial pathogens.