• Title/Summary/Keyword: signature-based detection

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Study on Distortion Ratio Calculation of Park's Vector Pattern for Diagnosis of Stator Winding Fault of Induction Motor (유도전동기의 고정자 권선고장 진단을 위한 팍스벡터 패턴의 왜곡률 연산에 대한 연구)

  • Yang, Chul-Oh;Park, Kyu-Nam;Song, Myung-Hyun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.4
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    • pp.643-649
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    • 2012
  • The diagnosis technique of stator winding faults based on Motor Current Signature Analysis(MCSA) was suggested. Park's vector pattern, the circle that is drawn by d-q transformed currents($i_d$, $i_q$), is widely used for stator winding faults detection. The current Distortion Ratio(DR), defined by the ratio of max axis and min axis of ellipse of Park's vector's pattern, was more simple and powerful method than the Park's vector pattern. In this study, a calculation method of distortion ratio of Park's vector pattern was suggested for auto diagnosis of stator winding short fault and usefulness of suggested calculation method of distortion ratio was verified through simulation using LabVIEW program.

A New S/W Architecture for YARA Speed Enhancement (YARA 속도 개선을 위한 새로운 S/W 구조설계)

  • Kim, Chang Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.12
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    • pp.1858-1860
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    • 2016
  • In this paper, a modified YARA software architecture that can perform pattern matching for multi-rule files is proposed. Based on a improved scanning thread algorithm, the new design reduces memory loading time of rule files for pattern matching. Therefore, the proposed architecture can reduce operation time for pattern matching while it requires an increased memory in proportion to the number of rule files.

The packer detection signature generation based on unpacking algorithm characteristic (Unpacking 알고리즘 특징 기반의 Packer 탐지 시그니처 생성 방안)

  • Shin, Dong-Hwi;Im, Chae-Tae;Jeong, Hyun-Cheol
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06d
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    • pp.56-60
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    • 2010
  • 악성코드의 기능들이 날로 정교해 지면서 악성 행위를 숨기거나 악성코드 분석이 어렵도록 만들기 위한 기법들이 적용되는 것을 쉽게 볼 수 있다. 이 중 악성코드 분석을 어렵게 만드는 대표적인 방식이 Packing이다. 그러므로 악성코드의 분석을 위해 Packing된 악성코드가 어떤 Packer로 Packing되어 있는 지 확인할 필요가 있다. 그러나 현재 사용하는 대부분의 시그니처 기반 탐지 방식은 오탐율 및 미탐율이 높다. 본 논문에서는 Packer 탐지를 위한 새로운 시그니처 생성 방식을 제안하고 성능을 검증한다.

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Computationally Efficient Rotor Fault Detection Algorithm Based on Motor Current Signature Analysis (효율적인 MCSA 기반 회전자 고장 검출 알고리즘)

  • Jeong, Chun-Ho;Song, Myung-Hyun;Kang, Eui-Sung;Kim, Kyung-Min
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2310-2312
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    • 2002
  • 전류 신호에 대한 고속 퓨리에 변환(FFT)은 유도전동기의 고장 검출에 널리 사용되어 왔다. 본 논문에서는 고정자 전류 스펙트럼 중에서 회전자 고장에 의해서 많은 영향을 받는 주파수 성분들로 특징 벡터를 구성하고, 이를 단순한 산술 연산만으로 처리함으로써 회전자 고장을 검출한다. 제안한 방법에서는 고장의 유무를 검출하기 위해서 기준 벡터와 입력 고정자 전류 신호로부터 추출된 특징 벡터 간의 차이 신호만을 이용하기 때문에 신경망에 의한 고장 검출 알고리즘 등에 비해서 훨씬 적은 계산량 만으로도 모터의 고장을 효율적으로 검출할 수 있다.

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Web-based Real Time Failure Diagnosis System Development for Induction Motor Bearing (유도전동기 베어링의 원거리 실시간 결함진단시스템 개발)

  • Kwon, Oh-Heon;Lee, Seung-Hyun
    • Journal of the Korean Society of Safety
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    • v.20 no.3 s.71
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    • pp.1-8
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    • 2005
  • The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.

A Probabilistic Test based Detection Scheme against Automated Attacks on Android In-app Billing Service

  • Kim, Heeyoul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1659-1673
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    • 2019
  • Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.

Multi Signature Based Polymorphic Worm Detection (다중 시그니쳐에 기반한 변형웜 탐지 기법)

  • Lee, Injoon;Song, Chihwan;Kang, Jaewoo
    • Annual Conference of KIPS
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    • 2010.11a
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    • pp.1252-1255
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    • 2010
  • 기존의 단일 시그니쳐를 이용한 악성 코드 침입 탐지 시스템은 자신의 컨텐츠를 변형시키는 변형웜을 잡기에는 적합하지 않다. 변형웜을 탐지하기 위한 노력으로 변형웜에 적합한 시그니쳐를 만들기 위한 노력이 있어왔다. 이 연구는 기존의 변형웜 탐지 시그니쳐 방법들을 분석하고 비교하여, 상호 보완적인 멀티 시그니쳐 방법을 제안한다. 이 방법은 정확도 높은 변형웜 탐지 시스템을 구성하기 위한 근본 기술로 활용될 것으로 기대한다.

New surveillance concepts in food safety in meat producing animals: the advantage of high throughput 'omics' technologies - A review

  • Pfaffl, Michael W.;Riedmaier-Sprenzel, Irmgard
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.7
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    • pp.1062-1071
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    • 2018
  • The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the 'transcriptome' has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern 'omics' and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid 'biomarker signature' can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional 'biomarker signatures' based on the physiological response triggered by illegal substances.

Adaptive Intrusion Detection Algorithm based on Learning Algorithm (학습 알고리즘 기반의 적응형 침입 탐지 알고리즘)

  • Sim, Kwee-Bo;Yang, Jae-Won;Lee, Dong-Wook;Seo, Dong-Il;Choi, Yang-Seo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.75-81
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    • 2004
  • Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn`t make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

Smart PZT-interface for wireless impedance-based prestress-loss monitoring in tendon-anchorage connection

  • Nguyen, Khac-Duy;Kim, Jeong-Tae
    • Smart Structures and Systems
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    • v.9 no.6
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    • pp.489-504
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    • 2012
  • For the safety of prestressed structures such as cable-stayed bridges and prestressed concrete bridges, it is very important to ensure the prestress force of cable or tendon. The loss of prestress force could significantly reduce load carrying capacity of the structure and even result in structural collapse. The objective of this study is to present a smart PZT-interface for wireless impedance-based prestress-loss monitoring in tendon-anchorage connection. Firstly, a smart PZT-interface is newly designed for sensitively monitoring of electro-mechanical impedance changes in tendon-anchorage subsystem. To analyze the effect of prestress force, an analytical model of tendon-anchorage is described regarding to the relationship between prestress force and structural parameters of the anchorage contact region. Based on the analytical model, an impedance-based method for monitoring of prestress-loss is conducted using the impedance-sensitive PZT-interface. Secondly, wireless impedance sensor node working on Imote2 platforms, which is interacted with the smart PZT-interface, is outlined. Finally, experiment on a lab-scale tendon-anchorage of a prestressed concrete girder is conducted to evaluate the performance of the smart PZT-interface along with the wireless impedance sensor node on prestress-loss detection. Frequency shift and cross correlation deviation of impedance signature are utilized to estimate impedance variation due to prestress-loss.