• International Journal of Internet, Broadcasting and Communication
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• 제7권2호
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• pp.56-64
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• 2015

The personal image information compiled through closed-circuit television (CCTV) will be open to the internet with the technology such as Long-Tail, Mash-Up, Collective Intelligence, Tagging, Open Application Programming Interface (Open-API), Syndication, Podcasting and Asynchronous JavaScript and XML (AJAX). The movie User Created Contents (UCC) connected to the internet with the skill of web 2.0 has the effects of abuse and threat without precedent. The purpose of this research is to develop the institutional and technological method to reduce these effects. As a result of this research, in terms of technology this paper suggests Privacy Zone Masking, IP Filtering, Intrusion-detection System (IDS), Secure Sockets Layer (SSL), public key infrastructure (PKI), Hash and PDF Socket. While in terms of management this paper suggests Privacy Commons and Privacy Zone. Based on CCTV-UCC linked to the above network, the research regarding personal image information security is expected to aid in realizing insight and practical personal image information as a specific device in the following research.

• 한국컴퓨터정보학회논문지
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• 제11권6호
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• pp.211-219
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• 2006

무선 네트워크의 확대로 무선 트래픽에 대한 침입 탐지/차단 시스템의 필요성이 강조되고 있다. 본 연구에서는 캠퍼스 망에서 무선망을 통하여 유선망을 공격하는 트래픽들을 탐지하고 분석된 결과를 통합적으로 관리하여 공격 트래픽을 효과적으로 차단하는 시스템을 제안한다. 제안하는 시스템은 무선 트래픽의 침입 탐지를 위해 기존의 W-Sensor 기능을 소프트웨어 형태로 개발하고 탐지된 공격 트래픽을 차단하는 통합 보안 관리 시스템 W-TMS를 개발하여 연동하게 하였다. 개발된 W-Sensor SW를 통해 무선 트래픽의 공격에 대해 효율적인 탐지 기능을 수행하고 변화되는 공격 유형에 대해 신속하게 대응할 수 있다. 또한 노트북 등에 SW를 설치함으로써 기존 AP 기반 시스템에 비해 이동성을 증가시킬 수 있다.

• 대한안전경영과학회지
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• 제14권3호
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• pp.183-191
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• 2012

Since June 25th 1950, the beginning of the cold war (Korean war), Korean peninsula is still in a state of war. Officially South and North Korean government call a truceafter three years from the beginning day, however both countries are still having several combats in these days. So every Korean citizen male has duty for serving military duty and this lasts even after the serving regular military force, as reserved military. Although South Korea is very small country, the size of military is very large so informing all reserved military takes some time. Since this nation is confronting the enemy and considering the global potential threat, South Korean military needs expedite informing system to call up the reserved military to active duty. In this project, the current informing system has been analyzed and compared with the new method which is using social network service such as Twitter. However mobilization order is very critical. So in our new model there are two ways combined. Using twitter to inform and then use traditional ways to finish the order. This method will provide more efficient and accurate way to cover the call ups.

• 한국멀티미디어학회논문지
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• 제18권1호
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• pp.35-41
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• 2015

SDN(Software Defined Networking) has been considered as a new future computer network architecture and DDoS(Distributed Denial of Service) is the biggest threat in the network security. In SDN architecture, we present the technique to defend the DDoS SYN Flooding attack that is one of the DDoS attack method. First, we monitor the Backlog queue in order to reduce the unnecessary monitoring resources. If the Backlog queue of the certain server is occupied over 70%, the sFlow performs packet sampling with the server address as the destination address. To distinguish between the attacker and the normal user, we use the source address. We decide the SYN packet threshold using the remaining Backlog queue that possible to allow the number of connections. If certain sources address send the SYN packet over the threshold, we judge that this address is attacker. The controller will modify the flow table entry to block attack traffics. By using this method, we reduce the resource consumption about the unnecessary monitoring and the protection range is expanded to all switches. The result achieved from our experiment show that we can prevent the SYN Flooding attack before the Backlog queue is fully occupied.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4072-4079
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• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.101-109
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• 2021

Cybercrimes are the biggest threat that can influence the future of e-commerce, particularly in difficult times such as the COVID-19 pandemic. This pandemic has resulted in noticeable changes in e-customer behaviour represented in three types: spending rates, types of goods bought, and the number of purchasing times. Moreover, the percentage of cybercrime in many countries, including Saudi Arabia, has increased during the pandemic. The increase in the number of cybercrimes during the COVID-19 crisis and the changes in consumer behaviour shows that there is an urgent need to conduct research on the factors that have led to this. This study will explore the most significant factors that have an effect on the unexpected change of customer behaviour and cybercrime perceived risk during the COVID-19 pandemic in Saudi Arabia. The finding of the study will hopefully contribute to attempts in finding safer methods for shopping online during COVID-19 and similar crisis.

• 정보보호학회논문지
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• 제22권3호
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• pp.537-544
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• 2012

최근 무선 전산망 인프라를 발판으로 스마트폰의 사용자가 크게 증가하고 있다. 이와 함께 스마트폰의 악성코드도 함께 급증하여 개인정보 유출, 과금 부과 등의 피해가 속출하고 있다. 무선전산망 환경의 보안 위협에 대처하기 위해 WIPS, MDM과 같은 무선 전산망 및 무선 단말 기기를 관리하기 위한 솔루션이 시판되고 있으나 이는 기업이나 대규모 사업자를 위한 솔루션으로 일반 스마트폰 사용자에게는 제한적이며 다양한 경로로 유포되는 알려지지 않은 악성코드를 탐지하는데 어려움이 있다. 본 논문에서는 악성코드 유형에 따른 행위 분석을 바탕으로 스마트폰 시스템 점검을 수행하여 악성 코드 감염 여부를 판별할 수 있는 기초 자료를 제공하며, 악성 코드 확산을 방지하기 위한 블랙리스트 관리 기능, 악성코드 채증 기능이 포함된 모바일 보안 진단 시스템을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.3029-3042
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• 2022

For over half a century, the United States (US) and its coalition military aircrafts have been using Ultra High Frequency (UHF) band analog modulation (AM) radios in ground-to-air communication and short-range air-to-air communications. Evolving from this, since 2007, the US military and the North Atlantic Treaty Organization (NATO) adopted HAVE QUICK to be used by almost all aircrafts, because it had been revealed that intercepting and jamming of former aircraft communication signals was possible, which placed a serious threat to defense systems. The second-generation Anti-jam Tactical UHF Radio for NATO (SATURN) was developed to replace HAVE QUICK systems by 2023. The NATO Standardization Agreement (STANAG) 4372 is a classified document that defines the SATURN technical and operational specifications. In preparation of this future upgrade to SATURN systems, in this paper, the SATURN technical and operational specifications are reviewed, and the network synchronization, frequency hopping, and communication setup parameters that are controlled by the Network (NET) Time, Time Of Day (TOD), Word Of Day (WOD), and Multiple Word of Day (MWOD) are described in addition to SATURN Edition 3 (ED3) and future Edition 4 (ED4) basic features. In addition, an anti-jamming performance analysis (in reference to partial band jamming and pulse jamming) and the time delay queueing model analysis are conducted based on a SATURN transmitter and receiver assumed model.