• Title/Summary/Keyword: Anomaly Signal Detection

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Antitank Mine Detection with Geophysical Prospecting (물리탐사를 이용한 대전차 지뢰 탐지)

  • Cho, Seong-Jun;Kim, Jung-ho;Son, Jeong-Sul;Bang, Eun-Seok;Kim, Jong-Wook
    • 한국지구물리탐사학회:학술대회논문집
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    • 2007.06a
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    • pp.219-224
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    • 2007
  • We conducted geophysical surveys to detect antitank mine at Namji-eup, Gyeongsangnam-do which had been installed during Korean war. The surveys consisted of 2 stages, at the first stage we divided the survey area into 7 block and carried out magnetic gradient survey and GEM-3 EM survey sequentially for each block. Hence we verified anomaly areas using an excavator and a metal detector. Most of anomalies were found to be garbages such as trash cans, metallic wastes, and so on. And also, the concrete pipe was found at depth of 1 m, which had not referred in any report of that area. At the second stage, after trenching the covered soil down to 75 cm the same surveys were conducted. We could not find the strong signal to be inferred from a antitank mine, but we pointed out some anomalies to need careful handling because demining is very dangerous work even though there is few possibility that is mine.

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A Study on Detection Technique of Anomaly Signal for Financial Loan Fraud Based on Social Network Analysis (소셜 네트워크 분석 기반의 금융회사 불법대출 이상징후 탐지기법에 관한 연구)

  • Wi, Choong-Ki;Kim, Hyoung-Joong;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.4
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    • pp.851-868
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    • 2012
  • After the financial crisis in 2008, the financial market still seems to be unstable with expanding the insolvency of the financial companies' real estate project financing loan in the aftermath of the lasted real estate recession. Especially after the illegal actions of people's financial institutions disclosed, while increased the anxiety of economic subjects about financial markets and weighted in the confusion of financial markets, the potential risk for the overall national economy is increasing. Thus as economic recession prolongs, the people's financial institutions having a weak profit structure and financing ability commit illegal acts in a variety of ways in order to conceal insolvent assets. Especially it is hard to find the loans of shareholder and the same borrower sharing credit risk in advance because most of them usually use a third-party's name bank account. Therefore, in order to effectively detect the fraud under other's name, it is necessary to analyze by clustering the borrowers high-related to a particular borrower through an analysis of association between the whole borrowers. In this paper, we introduce Analysis Techniques for detecting financial loan frauds in advance through an analysis of association between the whole borrowers by extending SNA(social network analysis) which is being studied by focused on sociology recently to the forensic accounting field of the financial frauds. Also this technique introduced in this pager will be very useful to regulatory authorities or law enforcement agencies at the field inspection or investigation.

Detecting Jamming Attacks in MANET (MANET에서의 전파방해 공격 탐지)

  • Shrestha, Rakesh;Lee, Sang-Duk;Choi, Dong-You;Han, Seung-Jo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.3
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    • pp.482-488
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    • 2009
  • Mobile Ad-hoc Networks provide communication without a centralized infrastructure, which makes them suitable for communication in disaster areas or when quick deployment is needed. On the other hand, they are susceptible to malicious exploitation and have to face different challenges at different layers due to its open Ad-hoc network structure which lacks previous security measures. Denial of service (DoS) attack is one that interferes with the radio transmission channel causing a jamming attack. In this kind of attack, an attacker emits a signal that interrupts the energy of the packets causing many errors in the packet currently being transmitted. In harsh environments where there is constant traffic, a jamming attack causes serious problems; therefore measures to prevent these types of attacks are required. The objective of this paper is to carry out the simulation of the jamming attack on the nodes and determine the DoS attacks in OPNET so as to obtain better results. We have used effective anomaly detection system to detect the malicious behaviour of the jammer node and analyzed the results that deny channel access by jamming in the mobile Ad-hoc networks.

Seismic AVO Analysis, AVO Modeling, AVO Inversion for understanding the gas-hydrate structure (가스 하이드레이트 부존층의 구조파악을 위한 탄성파 AVO 분석 AVO모델링, AVO역산)

  • Kim Gun-Duk;Chung Bu-Heung
    • 한국신재생에너지학회:학술대회논문집
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    • 2005.06a
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    • pp.643-646
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    • 2005
  • The gas hydrate exploration using seismic reflection data, the detection of BSR(Bottom Simulating Reflector) on the seismic section is the most important work flow because the BSR have been interpreted as being formed at the base of a gas hydrate zone. Usually, BSR has some dominant qualitative characteristics on seismic section i.e. Wavelet phase reversal compare to sea bottom signal, Parallel layer with sea bottom, Strong amplitude, Masking phenomenon above the BSR, Cross bedding with other geological layer. Even though a BSR can be selected on seismic section with these guidance, it is not enough to conform as being true BSR. Some other available methods for verifying the BSR with reliable analysis quantitatively i.e. Interval velocity analysis, AVO(Amplitude Variation with Offset)analysis etc. Usually, AVO analysis can be divided by three main parts. The first part is AVO analysis, the second is AVO modeling and the last is AVO inversion. AVO analysis is unique method for detecting the free gas zone on seismic section directly. Therefore it can be a kind of useful analysis method for discriminating true BSR, which might arise from an Possion ratio contrast between high velocity layer, partially hydrated sediment and low velocity layer, water saturated gas sediment. During the AVO interpretation, as the AVO response can be changed depend upon the water saturation ratio, it is confused to discriminate the AVO response of gas layer from dry layer. In that case, the AVO modeling is necessary to generate synthetic seismogram comparing with real data. It can be available to make conclusions from correspondence or lack of correspondence between the two seismograms. AVO inversion process is the method for driving a geological model by iterative operation that the result ing synthetic seismogram matches to real data seismogram wi thin some tolerance level. AVO inversion is a topic of current research and for now there is no general consensus on how the process should be done or even whether is valid for standard seismic data. Unfortunately, there are no well log data acquired from gas hydrate exploration area in Korea. Instead of that data, well log data and seismic data acquired from gas sand area located nearby the gas hydrate exploration area is used to AVO analysis, As the results of AVO modeling, type III AVO anomaly confirmed on the gas sand layer. The Castagna's equation constant value for estimating the S-wave velocity are evaluated as A=0.86190, B=-3845.14431 respectively and water saturation ratio is $50\%$. To calculate the reflection coefficient of synthetic seismogram, the Zoeppritz equation is used. For AVO inversion process, the dataset provided by Hampson-Rushell CO. is used.

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Analysis on Normal Ionospheric Trend and Detection of Ionospheric Disturbance by Earthquake (정상상황 전리층 경향 분석 및 지진에 의한 전리층 교란검출)

  • Kang, Seonho;Song, Junesol;Kim, O-jong;Kee, Changdon
    • Journal of Advanced Navigation Technology
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    • v.22 no.2
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    • pp.49-56
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    • 2018
  • As the energy generated by earthquake, tsunami, etc. propagates through the air and disturbs the electron density in the ionosphere, the perturbation can be detected by analyzing the ionospheric delay in satellite signal. The electron density in the ionosphere is affected by various factors such as solar activity, latitude, season, and local time. To distinguish from the anomaly, therefore, it is required to inspect the normal trend of the ionosphere. Also, as the perturbation magnitude diminishes by distance it is necessary to develop an appropriate algorithm to detect long-distance disturbances. In this paper, normal condition ionosphere trend is analyzed via IONEX data. We selected monitoring value that has no tendency and developed an algorithm to effectively detect the long-distance ionospheric disturbances by using the lasting characteristics of the disturbances. In the end, we concluded the $2^{nd}$ derivative of ionospheric delay would be proper monitoring value, and the false alarm with the developed algorithm turned out to be 1.4e-6 level. It was applied to 2011 Tohoku earthquake case and the ionospheric disturbance was successfully detected.