• Korean Journal of Remote Sensing
• /
• v.37 no.5_2
• /
• pp.1317-1328
• /
• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• Journal of the Society of Disaster Information
• /
• v.10 no.1
• /
• pp.33-39
• /
• 2014

Chemical accidents are the cause of the accident site during the initial responders to quickly and easily see materials and concentration method for the U.S. Environmental Protection Agency(EPA) is widely used in the initial response team direct reading detection equipment used. Ministry of the tubular gas detection equipment to detect direct reading detection equipment used in the event of an accident scene, and shell-and-tube gas detector for rapid detection and identification and precise analysis of causative pollutants before about strategically can identify the quantitative and qualitative useful equipment. However, those who initially respond to the scene of a direct reading detection equipment and a simple lack of understanding of how to use the numbers only because of the way you want to check the accuracy of detection results have been raising questions about the increase. The scene of the accident in order to obtain an accurate detection results used in this paper, the Ministry of Environment of gas detectors detect tubular Kitagawa and Draeger detector tube to check the reactivity of the material on-site detection of early response of those who were to raise the accuracy of the results.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.499-504
• /
• 2006

터널 내 화재 발생 시 대규모의 인명, 재산 피해가 발생하는데 이러한 상황을 조기에 탐지함으로써 피해를 최소화하기 위한 시스템이 필요하다. 또한 터널 내 설치된 CCTV를 사람이 24시간 감시하기에는 너무 어려운 점이 많다. 이에 따라 적절한 영상 처리를 통한 화염 및 연기 검출 시스템을 통해 경보를 알려줄 경우, 보다 편리하고 사람이 모니터 앞에 없을 때 화재 발생 시 화재를 검출할 수 있어 피해를 최소화 할 수 있다. 본 논문에서는 영상처리 기법을 이용하여 터널 안에서 발생한 화재 및 연기를 고속으로 탐지하기 위한 알고리즘을 제안하였다. 터널 안에서의 화재 탐지는 차량 조명 및 터널내의 조명등과 같은 여러 가지 상황에 의해 산불 탐지 알고리즘과 다른 독자적인 알고리즘의 개발이 요구된다. 본 논문에서 제시한 두 가지 알고리즘은 기존 알고리즘보다 정확한 위치 탐지와 초기 단계에서의 탐지가 가능하도록 되었다. 또한 우리는 실험 결과를 통해 각각의 성능을 비교함으로써 제시한 알고리즘의 타당성을 보여주었다.

• Annual Conference of KIPS
• /
• 2024.10a
• /
• pp.265-266
• /
• 2024

오픈 소스 소프트웨어 공급망의 성장과 함께 악성 패키지 탐지가 중요한 과제가 되고 있다. 기존의 정적 분석과 동적 분석은 시간이 많이 소요되기 때문에, 본 연구에서는 이를 해결하기 위해 메타데이터 분석을 도입했다. 또한, 외부 메타데이터에 의존하는 기존 탐지 모델의 한계를 극복하고자, 내부 메타데이터만을 활용하여 배포 초기에도 RubyGems 에서 악성 패키지를 신속하게 탐지할 수 있는 모델을 제안한다. 실험 결과, 제안한 모델은 평균 97.63%의 정확도로 우수한 성능과 빠른 탐지 속도를 보여, 내부 메타데이터 기반의 탐지 방식의 가능성을 확인하였다.

• Science of Emotion and Sensibility
• /
• v.15 no.1
• /
• pp.37-46
• /
• 2012

We tested the effects of endogenous attention and reorienting on the performance of detection task. In the classic detection paradigm of Posner and Cohen (1980), performance on target detection is measured, where target appears either on the same or difference spatial location of cue stimulus after brief period of SOA (stimulus onset asynchrony). In this study, we induced exogenous attention by manipulating predictability of cue for target, and also induced reorientation by inserting additional (reorienting) cue between initial cue and target. Experiment 1 had three conditions of reorienting speed: Early, middle, and late. Facilitation and IOR (inhibition of return) occurred in different forms depending on SOA and reorienting speed, but we were not able to discover interpretable pattern in the results. However, reanalysis of early reorienting condition revealed that facilitation and IOR occurred in a crossed manner where short SOA found facilitation and long SOA did IOR, the typical results of simple detection task. Experiment 2 collected additional data to replicate the results in early reorienting condition of experiment 1. The results obtained that facilitation occurred with short SOA and IOR with long SOA. These results contrast with those of Wright and Richard (2000) where they reported elimination of IOR when cue had predictability of target locations. These results suggest that additional cue (here, orienting cue), which rapidly appears before extinction of IOR by prior cue, brings about double IOR. The present research demonstrates that even when attention is allocated to certain location via endogenous mechanism, rapidly repeating cues in certain location maximizes IOR that offsets the effects of endogenous attention to the same location.

• Journal of KIISE:Information Networking
• /
• v.35 no.6
• /
• pp.474-481
• /
• 2008

Scanning worm increases network traffic load and result in severe network congestion because it is a self-replicating worm and send copies of itself to a number of hosts through the Internet. So an early detection system which can automatically detect scanning worms is needed to protect network from those attacks. Although many studies are conducted to detect scanning worms, most of them are focusing on the method using packet header information. The method using packet header information has long detection delay since it must examine the header information of all packets entering or leaving the network. Therefore we propose an algorithm to detect scanning worms using network traffic characteristics such as variance of traffic volume, differentiated traffic volume, mean of differentiated traffic volume, and product of mean traffic volume and mean of differentiated traffic volume. We verified the proposed algorithm by analyzing the normal traffic captured in the real network and the worm traffic generated by simulator. The proposed algorithm can detect CodeRed and Slammer which are not detected by existing algorithm. In addition, all worms were detected in early stage: Slammer was detected in 4 seconds and CodeRed and Witty were detected in 11 seconds.

• Review of KIISC
• /
• v.15 no.2
• /
• pp.74-82
• /
• 2005

오늘날 네트워크 보안 기술은 해커의 침입 탐지 및 제어, 분산 서비스 거부 공격의 방지 등 많은 분야에서 발전하여 왔다. 그러나, 최근 많은 문제를 발생시키면서 등장한 인터넷 웜은 기존의 네트워크 보안 장비들을 무력화시키며 인터넷 상에 연결된 많은 호스트들을 감염시키고 동시에 네트워크 자원을 소모시켜 버렸다. 실상 초기의 웜은 작은 규모의 네트워크에서 퍼지는 정도 일뿐 심각한 피해를 주는 경우는 거의 없었고 따라서 이에 대해서 심각한 대비책 등을 생각하지는 않았다. 그러나 2001년 발생한 CodeRed 웜은 인터넷에 연결된 많은 컴퓨터들을 순식간에 감염시켜 많은 경제적, 물질적 피해를 발생시켰고, 그 이후 2003년 1월에 발생한 Stammer 웜은 10분이라는 짧은 순간 안에 75000 여대 이상의 호스트를 감염시키고 네트워크 자체를 마비시켰다. 특히 Stammer 월은 국내에서 많은 피해를 유발시켰기에 더더욱 유명하다. 명절 구정과 맞물려 호황을 누리던 인터넷 쇼핑 몰과, 인터넷 금융 거래를 수행하던 은행 전산소 등을 일시에 마비시켜 버리면서 경제적으로도 실질적인 막대한 피해를 우리에게 주었다. 이런 웜을 막기 위해서 많은 보안 업체 및 연구소들이 나서고 있으나, 아직은 사전에 웜의 피해를 막을만한 확실한 대답을 얻지 못하고 있다. 본 논문에서는, 현재 수행하고 있는 여러 웜의 탐지기법에 대해서 조사한 결과를 설명하고, 이어서 본 연구소에서 수행하고 있는 웜의 탐지 기법에 대해서 설명하고 간단한 탐지 결과를 보일 것이다.

• Proceedings of the Korea Contents Association Conference
• /
• 2003.11a
• /
• pp.144-148
• /
• 2003

A general administrator's response ability plunged in confusion as intrusion detection system like an existing Snort display much alert messages on administrator's screen. Also, there are some possibilities to cause false positive. In this paper, to solve these problems, we designed Web-based ID(Intrusion Detection) traffic analysis system using correlation, and implemented so that administrator can check easily whole intrusion traffic state in web which dividing into normal and intrusion traffic using Libpcap, Snort, ACID, Nmap and Nessus. As a simulation result, it is proved that alert message number and false positive rate are minimized.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.9
• /
• pp.445-456
• /
• 2017

In this paper, we propose a method to detect spam tweets containing unhealthy information by using an n-gram dictionary under limited labeling. Spam tweets that contain unhealthy information have a tendency to use similar words and sentences. Based on this characteristic, we show that spam tweets can be effectively detected by applying a Naive Bayesian classifier using n-gram dictionaries which are constructed from spam tweets and normal tweets. On the other hand, constructing an initial training set requires very high cost because a large amount of data flows in real time in a twitter. Therefore, there is a need for a spam detection method that can be applied in an environment where the initial training set is very small or non exist. To solve the problem, we propose a method to generate pseudo-labels by utilizing twitter's retweet function and use them for the configuration of the initial training set and the n-gram dictionary update. The results from various experiments using 1.3 million korean tweets collected from December 1, 2016 to December 7, 2016 prove that the proposed method has superior performance than the compared spam detection methods.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.36 no.5
• /
• pp.345-352
• /
• 2016

As aircrafts are being operated at high altitude, wing structures experience various fatigue loadings under cryogenic environments. As a result, fatigue damage such as a crack could be develop that could eventually lead to a catastrophic failure. For this reason, fatigue damage monitoring is an important process to ensure efficient maintenance and safety of structures. To implement damage detection in real-world flight environments, a special cooling chamber was built. Inside the chamber, the temperature was maintained at the cryogenic temperature, and harmonic fatigue loading was given to a wing structure. In this study, piezoelectric active-sensing based guided waves were used to detect the fatigue damage. In particular, a beamforming technique was applied to efficiently measure the scattering wave caused by the fatigue damage. The system was used for detection, growth monitoring, and localization of a fatigue crack. In addition, a sensor diagnostic process was also applied to ensure the proper operation of piezoelectric sensors. Several experiments were implemented and the results of the experiments demonstrated that this process could efficiently detect damage in such an extreme environment.