• 제목/요약/키워드: Detection Systems

검색결과 5,982건 처리시간 0.032초

Modeling of Positive Selection for the Development of a Computer Immune System and a Self-Recognition Algorithm

  • Sim, Kwee-Bo;Lee, Dong-Wook
    • International Journal of Control, Automation, and Systems
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    • 제1권4호
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    • pp.453-458
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    • 2003
  • The anomaly-detection algorithm based on negative selection of T cells is representative model among self-recognition methods and it has been applied to computer immune systems in recent years. In immune systems, T cells are produced through both positive and negative selection. Positive selection is the process used to determine a MHC receptor that recognizes self-molecules. Negative selection is the process used to determine an antigen receptor that recognizes antigen, or the nonself cell. In this paper, we propose a novel self-recognition algorithm based on the positive selection of T cells. We indicate the effectiveness of the proposed algorithm by change-detection simulation of some infected data obtained from cell changes and string changes in the self-file. We also compare the self-recognition algorithm based on positive selection with the anomaly-detection algorithm.

이산시간 상태지연 시스템을 위한 ℋ_/ℋ 고장검출 및 분리 (ℋ_/ℋ Fault Detection and Isolation for Discrete-Time Delayed Systems)

  • 지성철;이호재
    • 제어로봇시스템학회논문지
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    • 제17권10호
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    • pp.960-966
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    • 2011
  • In this paper, an $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ fault detection and isolation (FDI) observer design problem is investigated for discrete-time delayed systems. To that end, a bank consisting of the sensor's number of observers is introduced. Each residual should be sensitive to a certain partial group of faults, but robust against the disturbance as far as possible. We formulate this multiobjective FDI problem as $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ observers design problem. Sufficient design condition is expressed as iterative linear matrix inequalities. The fault is then detected and isolated by evaluating the residuals through an FDI decision logic. A computer simulation is provided for verification of the proposed technique.

Code-Reuse Attack Detection Using Kullback-Leibler Divergence in IoT

  • Ho, Jun-Won
    • International journal of advanced smart convergence
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    • 제5권4호
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    • pp.54-56
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    • 2016
  • Code-reuse attacks are very dangerous in various systems. This is because they do not inject malicious codes into target systems, but reuse the instruction sequences in executable files or libraries of target systems. Moreover, code-reuse attacks could be more harmful to IoT systems in the sense that it may not be easy to devise efficient and effective mechanism for code-reuse attack detection in resource-restricted IoT devices. In this paper, we propose a detection scheme with using Kullback-Leibler (KL) divergence to combat against code-reuse attacks in IoT. Specifically, we detect code-reuse attacks by calculating KL divergence between the probability distributions of the packets that generate from IoT devices and contain code region addresses in memory system and the probability distributions of the packets that come to IoT devices and contain code region addresses in memory system, checking if the computed KL divergence is abnormal.

Efficient Near-Optimal Detection with Generalized Sphere Decoder for Blind MU-MIMO Systems

  • Kim, Minjoon;Park, Jangyong;Kim, Hyunsub;Kim, Jaeseok
    • ETRI Journal
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    • 제36권4호
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    • pp.682-685
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    • 2014
  • In this letter, we propose an efficient near-optimal detection scheme (that makes use of a generalized sphere decoder (GSD)) for blind multi-user multiple-input multiple-output (MU-MIMO) systems. In practical MU-MIMO systems, a receiver suffers from interference because the precoding matrix, the result of the precoding technique used, is quantized with limited feedback and is thus imperfect. The proposed scheme can achieve near-optimal performance with low complexity by using a GSD to detect several additional interference signals. In addition, the proposed scheme is suitable for use in blind systems.

Stochastic Duels with Random Detection

  • Kwon, T.Y.;Bai, D.S.
    • Journal of the Korean Statistical Society
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    • 제7권2호
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    • pp.121-130
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    • 1978
  • This paper presents a method of incorporating detection capability of weapon systems into the "fundamental" stochastic duels of Williams and Ancker when both detection and interfiring times are continuous random variables. An example with negative exponential detection and firing times is also given.lso given.

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차량항법 시스템을 위한 소형 음성합성 엔진 (Speech synthesis engine for car navigation systems)

  • 김경하;서흥석;박찬식;성태경;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.338-338
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    • 2000
  • This paper proposes a modified TD-PSOLA algorithm for Korean speech synthesis. A WSS (Weighted score search) algorithm is proposed for pitch detection and speech synthesis engine is designed using 46 phones database.

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Detecting Malware in Cyberphysical Systems Using Machine Learning: a Survey

  • Montes, F.;Bermejo, J.;Sanchez, L.E.;Bermejo, J.R.;Sicilia, J.A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권3호
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    • pp.1119-1139
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    • 2021
  • Among the scientific literature, it has not been possible to find a consensus on the definition of the limits or properties that allow differentiating or grouping the cyber-physical systems (CPS) and the Internet of Things (IoT). Despite this controversy the papers reviewed agree that both have become crucial elements not only for industry but also for society in general. The impact of a malware attack affecting one of these systems may suppose a risk for the industrial processes involved and perhaps also for society in general if the system affected is a critical infrastructure. This article reviews the state of the art of the application of machine learning in the automation of malware detection in cyberphysical systems, evaluating the most representative articles in this field and summarizing the results obtained, the most common malware attacks in this type of systems, the most promising algorithms for malware detection in cyberphysical systems and the future lines of research in this field with the greatest potential for the coming years.

UAV를 활용한 미사일접근경보 장비의 탐지거리 시험결과 고찰 (Consideration of Detection Range Test Results of Missile Approach Warning Equipment using UAV)

  • 이병헌;권재언;김영일;이성일;이청;허장욱
    • 한국군사과학기술학회지
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    • 제27권2호
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    • pp.213-221
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    • 2024
  • Aircraft's operational effectiveness is reduced due to threats from enemy anti-aircraft weapons, which is a weak point. In particular, guided missiles, which pose a threat to aircraft, are rapidly developing due to technological advancements in seekers, and are classified as one of the important technologies in weapon systems. Missile approach warning equipment installed to ensure aircraft survivability detects guided missiles and provides relevant information to respond. Tests were conducted domestically to verify the detection level of missile approach warning equipment, and test results were presented under various test conditions.

카메라와 도로평면의 기하관계를 이용한 모델 기반 곡선 차선 검출 (Model-based Curved Lane Detection using Geometric Relation between Camera and Road Plane)

  • 장호진;백승해;박순용
    • 제어로봇시스템학회논문지
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    • 제21권2호
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    • pp.130-136
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    • 2015
  • In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results.

순차적 결함 검출 방법에 기반한 TFT-LCD 결함 영역 검출 (TFT-LCD Defect Blob Detection based on Sequential Defect Detection Method)

  • 이은영;박길흠
    • 한국산업정보학회논문지
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    • 제20권2호
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    • pp.73-83
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    • 2015
  • 본 논문에서는 순차적 결함 검출 방법을 이용하여 TFT-LCD의 결함 영역(Blob)을 효과적으로 검출하는 알고리즘을 제안한다. 먼저 결함과 배경 간의 휘도 차를 이용하여 영상의 각 화소들에 대한 결함 확률을 판단하고, 결함 확률에 따른 순차적 결함 검출 방법을 이용하여 결함 후보 화소를 검출한다. 여기서 결함 확률이란 결함 후보 화소가 검출된 단계에 따라 결함 영역에 포함될 가능성을 나타내다. 형태학 연산을 적용함으로써 검출된 후보 화소들을 후보 결함 영역으로 형성하고, 각 후보 결함 영역에 대한 결함 가능성을 계산하여 결함 영역을 검출한다. 모의 TFT-LCD 영상을 생성하여 제안 방법의 타당성을 검증하고, 실제 TFT-LCD 영상에 적용함으로서 제안 알고리즘의 우수한 결함 검출 성능을 확인하였다.