• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.243-250
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• 2019

In this paper, we propose a system for processing and analyzing drone image information which can be applied variously in disasters-security situation. The proposed system stores the images acquired from the drones in the server, and performs image processing and analysis according to various scenarios. According to each mission, deep-learning method is used to construct an image analysis system in the images acquired by the drone. Experiments confirm that it can be applied to traffic volume measurement, suspect and vehicle tracking, survivor identification and maritime missions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4246-4267
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• 2020

As the network goes deep into all aspects of people's lives, the number and the complexity of network traffic is increasing, and traffic classification becomes more and more important. How to classify them effectively is an important prerequisite for network management and planning, and ensuring network security. With the continuous development of deep learning, more and more traffic classification begins to use it as the main method, which achieves better results than traditional classification methods. In this paper, we provide a comprehensive review of network traffic classification based on deep learning. Firstly, we introduce the research background and progress of network traffic classification. Then, we summarize and compare traffic classification based on deep learning such as stack autoencoder, one-dimensional convolution neural network, two-dimensional convolution neural network, three-dimensional convolution neural network, long short-term memory network and Deep Belief Networks. In addition, we compare traffic classification based on deep learning with other methods such as based on port number, deep packets detection and machine learning. Finally, the future research directions of network traffic classification based on deep learning are prospected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4537-4556
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• 2020

This research was based on the study conducted by Khodaei et al. (2012), namely, the least-significant-bit (LSB) substitution combined with the pixel-value differencing (PVD) steganography, and presented an improved irreversible image steganography method. Such a method was developed through integrating the improved LSB substitution with the modulus function-based PVD steganography to increase steganographic capacity of the original technique while maintaining the quality of images. It partitions the cover image into non-overlapped blocks, each of which consists of 3 consecutive pixels. The 2nd pixel represents the base, in which secret data are embedded by using the 3-bit LSB substitution. Each of the other 2 pixels is paired with the base respectively for embedding secret data by using an improved modulus PVD method. The experiment results showed that the method can greatly increase steganographic capacity in comparison with other PVD-based techniques (by a maximum amount of 135%), on the premise that the quality of images is maintained. Last but not least, 2 security analyses, the pixel difference histogram (PDH) and the content-selective residual (CSR) steganalysis were performed. The results indicated that the method is capable of preventing the detection of the 2 common techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1871-1890
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• 2021

The transition toward a contactless society has been rapidly progressing owing to the recent COVID-19 pandemic. As a result, the IT environment of organizations and enterprises is changing rapidly; in particular, data security is expanding to the private sector. To adapt to these changes, organizations and companies have started to securely transfer confidential data to residential PCs and personally owned devices of employees working from home or from other locations. Therefore, organizations and companies are introducing streaming data services, such as the virtual desktop infrastructure (VDI) or cloud services, to securely connect internal and external networks. These methods have the advantage of providing data without the need to download to a third terminal; however, while the data are being streamed, attacks such as screen shooting or capturing are performed. Therefore, there is an increasing interest in prevention techniques against screen capture threats that may occur in a contactless environment. In this study, we analyze possible screen capture methods in a PC and a mobile phone environment and present techniques that can protect the screens against specific attack methods. The detection and defense for screen capture of PC applications on Windows OS and Mac OS could be solved with a single agent using our proposed techniques. Screen capture of mobile devices can be prevented by applying our proposed techniques on Android and iOS.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.45-56
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• 2022

The Ieodo Ocean Research Station (IORS) lies between the exclusive economic zone (EEZ) boundaries of Korea, Japan, and China. The geographical positioning of the IORS makes it ideal for monitoring ships in the area. In this study, we introduce ship monitoring results by Automatic Identification System (AIS) and the Broadband 3G^TM radar, which has been developed for use in small ships using the Frequency Modulated Continuous Wave (FMCW) technique. AIS and FMCW radar data were collected at IORS from November 23th to 30th, 2013. The acquired FMCW radar data was converted to 2-D binary image format over pre-processing, including the internal and external noise filtering. The ship positions detected by FMCW radar images were passed into a tracking algorithm. We then compared the detection and tracking results from FMCW radar with AIS information and found that they were relatively well matched. Tracking performance is especially good when ships are across from each other. The results also show good monitoring capability for small fishing ships, even those not equipped with AIS or with a dysfunctional AIS.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.221-236
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• 2022

BLE protocol prevents MITM attacks with user interaction through some input/output devices such as keyboard or display. Therefore, If it use a device which has no input/output facility, it can be vulnerable to MITM attack. If messages to be sent to a control device is forged by MITM attack, the device can be abnormally operated by malicious attack from attacker. Therefore, we describes a scenario which has the vulnerabilities of the BLE network in this paper and propose countermeasure method against MITM attacks integrity violations. Its mechanism provides data confidentiality and integrity with MD5 and security key distribution of Diffie Helman's method. In order to verify the effectiveness of the countermeasure method proposed in this paper, we have conducted the experiments. ​As experiments, the message was sent 200 times and all of them successfully detected whether there was MITM attack or not. In addition, it took at most about 4.2ms delay time with proposed countermeasure method between devices even attacking was going on. It is expected that more secure data transmission can be achieved between IoT devices on a BLE network through the method proposed.

• Review of KIISC
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• v.32 no.4
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• pp.7-17
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• 2022

운전자 보조 시스템을 통한 차량의 전자적인 제어를 위하여, 최근 차량에 탑재된 전자 제어 장치 (ECU; Electronic Control Unit)의 개수가 급증하고 있다. ECU는 효율적인 통신을 위해서 차량용 내부 네트워크인 CAN(Controller Area Network)을 이용한다. 하지만 CAN은 기밀성, 무결성, 접근 제어, 인증과 같은 보안 메커니즘이 고려되지 않은 상태로 설계되었기 때문에, 공격자가 네트워크에 쉽게 접근하여 메시지를 도청하거나 주입할 수 있다. 악의적인 메시지 주입은 차량 운전자 및 동승자의 안전에 심각한 피해를 안길 수 있기에, 최근에는 주입된 메시지를 식별하기 위한 침입 탐지 시스템(IDS; Intrusion Detection System)에 대한 연구가 발전해왔다. 특히 최근에는 AI(Artificial Intelligence) 기술을 이용한 IDS가 다수 제안되었다. 그러나 제안되는 기법들은 특정 공격 데이터셋에 한하여 평가되며, 각 기법에 대한 탐지 성능이 공정하게 평가되었는지를 확인하기 위한 평가 프레임워크가 부족한 상황이다. 따라서 본 논문에서는 machine learning/deep learning에 기반하여 제안된 차랑용 IDS 5가지를 선정하고, 기존에 공개된 데이터셋을 이용하여 제안된 기법들에 대한 비교 및 평가를 진행한다. 공격 데이터셋에는 CAN의 대표적인 4가지 공격 유형이 포함되어 있으며, 추가적으로 본 논문에서는 메시지 주기 유형을 활용한 공격 유형을 제안하고 해당 공격에 대한 탐지 성능을 평가한다.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3506-3513
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• 2023

In this paper, we demonstrate the neutron attenuation of dry cask shielding materials using the S670e helium-4 detector manufactured by Arktis Radiation Ltd. In particular, two materials expected to be applied to the TN-32 dry cask manufactured by ORANO Korea and KORAD-21 by the Korea Radioactive Waste Agency (KORAD) were utilized. The measured neutron attenuation was compared with our Monte Carlo N-Particle Transport simulation results, and the difference is given as the root mean square (RMS). For the fast neutron case, a rapid decline in neutron counts was observed as a function of increasing material thickness, exhibiting an exponential relationship. The discrepancy between the experimentally acquired data and simulation results for the fast neutron was maintained within a 2.3% RMS. In contrast, the observed thermal neutron count demonstrated an initial rise, attained a maximum value, and exhibited an exponential decline as a function of increasing thickness. In particular, the discrepancy between the measured and simulated peak locations for thermal neutrons displayed an RMS deviation of approximately 17.3-22.4%. Finally, the results suggest that a minimum thickness of 5 cm for Li-6 is necessary to achieve a sufficiently significant cross-section, effectively capturing incoming thermal neutrons within the dry cask.

• Analytical Science and Technology
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• v.19 no.1
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• pp.58-64
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• 2006

A mugwort-tissue-based modified carbon paste electrode was constructed for the amperometric detection of hydrogen peroxide and its electrochemical properties are described. Especially the amperometric signal was very stable and bigger than any other enzyme electrode studied in this lab. The effect of tissue composition on the response was linear within the wide range of experiment and the linearity of Lineweaver-Burk plot showed that the sensing process of the biosensor is by enzymatic catalysis. And pH dependent current profile connoted that two isozymes are active in this system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1249-1252
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• 2022

In this paper, we propose a conceptual framework that identifies video frames in motion containing the movement of people and vehicles in traffic videos. The automatic selection of video frames in motion is an important topic in security and surveillance video because the number of videos to be monitored simultaneously is simply too large due to limited human resources. The conventional method to identify the areas in motion is to compute the differences over consecutive video frames, which has been costly because of its high computational complexity. In this paper, we reduced the overall complexity by examining only the keyframes (or I-frames). The basic assumption is that the time period between I-frames is rather shorter (e.g., 1/10 ~ 3 secs) than the usual length of objects in motion in video (i.e., pedestrian walking, automobile passing, etc.). The proposed method estimates the possibility of videos containing motion between I-frames by evaluating the difference of consecutive I-frames with the long-time statistics of the previously decoded I-frames of the same video. The experimental results showed that the proposed method showed more than 80% accuracy in short surveillance videos obtained from different locations while keeping the computational complexity as low as 20 % compared to the HM decoder.