• Title/Summary/Keyword: system detection

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Intrusion Detection System Based on Multi-Class SVM (다중 클래스 SVM기반의 침입탐지 시스템)

  • Lee Hansung;Song Jiyoung;Kim Eunyoung;Lee Chulho;Park Daihee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.3
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    • pp.282-288
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    • 2005
  • In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This new intrusion detection system, named to MMIDS, was designed to satisfy all the following requirements : 1) Fast detection of new types of attack unknown to the system; 2) Provision of detail information about the detected types of attack; 3) cost-effective maintenance due to fast and efficient learning and update; 4) incrementality and scalability of system. The fast and efficient training and updating faculties of proposed novel multi-class SVM which is a core component of MMIDS provide cost-effective maintenance of intrusion detection system. According to the experimental results, our method can provide superior performance in separating similar patterns and detailed separation capability of MMIDS is relatively good.

Real-Time Landmark Detection using Fast Fourier Transform in Surveillance (서베일런스에서 고속 푸리에 변환을 이용한 실시간 특징점 검출)

  • Kang, Sung-Kwan;Park, Yang-Jae;Chung, Kyung-Yong;Rim, Kee-Wook;Lee, Jung-Hyun
    • Journal of Digital Convergence
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    • v.10 no.7
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    • pp.123-128
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    • 2012
  • In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

Numerical estimation on balance coefficients of central difference averaging method for quench detection of the KSTAR PF coils

  • Kim, Jinsub;An, Seok Chan;Ko, Tae Kuk;Chu, Yong
    • Progress in Superconductivity and Cryogenics
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    • v.18 no.3
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    • pp.25-29
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    • 2016
  • A quench detection system of KSTAR Poloidal Field (PF) coils is inevitable for stable operation because normal zone generates overheating during quench occurrence. Recently, new voltage quench detection method, combination of Central Difference Averaging (CDA) and Mutual Inductance Compensation (MIK) for compensating mutual inductive voltage more effectively than conventional voltage detection method, has been suggested and studied. For better performance of mutual induction cancellation by adjacent coils of CDA+MIK method for KSTAR coil system, balance coefficients of CDA must be estimated and adjusted preferentially. In this paper, the balance coefficients of CDA for KSTAR PF coils were numerically estimated. The estimated result was adopted and tested by using simulation. The CDA method adopting balance coefficients effectively eliminated mutual inductive voltage, and also it is expected to improve performance of CDA+MIK method for quench detection of KSTAR PF coils.

An Approach for Security Problems in Visual Surveillance Systems by Combining Multiple Sensors and Obstacle Detection

  • Teng, Zhu;Liu, Feng;Zhang, Baopeng;Kang, Dong-Joong
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1284-1292
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    • 2015
  • As visual surveillance systems become more and more common in human lives, approaches based on these systems to solve security problems in practice are boosted, especially in railway applications. In this paper, we first propose a robust snag detection algorithm and then present a railway security system by using a combination of multiple sensors and the vision based snag detection algorithm. The system aims safety at several repeatedly occurred situations including slope protection, inspection of the falling-object from bridges, and the detection of snags and foreign objects on the rail. Experiments demonstrate that the snag detection is relatively robust and the system could guarantee the security of the railway through these real-time protections and detections.

Fault Detection of Propeller of an Overactuated Unmanned Surface Vehicle based on Convolutional Neural Network (합성곱신경망을 활용한 과구동기 시스템을 가지는 소형 무인선의 추진기 고장 감지)

  • Baek, Seung-dae;Woo, Joo-hyun
    • Journal of the Society of Naval Architects of Korea
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    • v.59 no.2
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    • pp.125-133
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    • 2022
  • This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

Passive acoustic fish detection analysis and its feasible aspects (수동어탐의 가능성과 전망)

  • 장지원
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.22 no.4
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    • pp.98-103
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    • 1986
  • The passive acoustic system only has generally used in fish detection. But the passive acoustic system has not been tried in fishing since Freytag has proposed a possibilities of the passive detection of fishes in 1963. This paper describes the .feasible aspects of fish detection by listening of the sound they make. The passive acoustic system accompanied the active acoustic system may expand the range of detection and compensate for lack of capabilities each other, but there are some difficulties in noise rejection because the fre9uency range of ship noises covers the whole range vf biological sounds. The attempt to collect useful informations from underwater would be greatly contributed in fisheries.

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A Genetic Algorithm-Based Intrusion Detection System

  • Lee, Han H.;Lee, Duk;Kim, Hee S.;Park, Jong U.
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.04a
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    • pp.343-346
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    • 2000
  • In this paper, a novel approach to intruder detection is introduced. The approach, based on the genetic algorithms, improved detection rate of the host systems which has traditionally relied on known intruder patterns and host addresses. Rather than making judgments on whether the access is instrusion or not, the systems can continuously monitor systems with categorized security level. With the categorization, when the intruder attempts repeatedly to access the systems, the security level is incrementally escalated. In the simulation of a simple intrusion, it was shown that the current approach improves robustness of the security systems by enhancing detection and flexibility. The evolutionary approach to intruder detection enhances adaptability of the system.

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New approach to two wheelers detection using Cell Comparison

  • Lee, Yeunghak;Kim, Taesun;Lee, Sanghoon;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.1 no.1
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    • pp.45-53
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    • 2014
  • This article describes a two wheelers detection system riding on people based on modified histogram of oriented gradients (HOG) for vision based intelligent vehicles. These features used correlation coefficient parameter are able to classify variable and complicated shapes of a two wheelers according to different viewpoints as well as human appearance. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. In this paper, we propose an evolutionary method trained part-based models to classify multiple view-based detection: frontal, rear and side view (within $60^{\circ}C$). Our experimental results show that a two wheelers riding on people detection system based on proposed approach leads to higher detection accuracy rate than traditional features.

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Performance Evaluation of a BACnet-based Fire Detection and Monitoring System for use in Buildings

  • Song Won-Seok;Hong Seung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.1
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    • pp.70-76
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    • 2006
  • The objective of this paper is to propose a reference model of a fire detection and monitoring system using MS/TP protocol. The reference model is designed to satisfy the requirements of response time and flexibility. The reference model is operated on the basis of BACnet, a standard communication protocol for building automation systems. Validity of the reference model was examined using a simulation model. This study also evaluated the performance of the BACnet-based fire detection and monitoring system in terms of network-induced delay. Simulation results show that the reference model satisfies the requirements of the fire detection and monitoring system.

A Criterion on Profiling for Anomaly Detection (이상행위 탐지를 위한 프로파일링 기준)

  • 조혁현;정희택;김민수;노봉남
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.3
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    • pp.544-551
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    • 2003
  • Internet as being generalized, intrusion detection system is needed to protect computer system from intrusions synthetically. We propose a criterion on profiling for intrusion detection system using anomaly detection. We present the cause of false positive on profiling and propose anomaly method to control this. Finally, we propose similarity function to decide whether anomaly action or not for user pattern using pattern database.