• ETRI Journal
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• 제39권1호
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• pp.124-134
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• 2017

Data races are one of the most difficult types of bugs in concurrent multithreaded systems. It requires significant time and cost to accurately detect bugs in complex large-scale programs. Although many race detection techniques have been proposed by various researchers, none of them are effective in all aspects. In this paper, we compare the performance of five recent dynamic race detection techniques: FastTrack, Acculock, Multilock-HB, SimpleLock+, and causally precedes (CP) detection. We experimentally demonstrate the strengths and weaknesses of these dynamic race detection techniques in terms of their detection capability, running time, and runtime overhead using 20 benchmark programs with different characteristics. The comparison results show that the detection capability of CP detection does not differ from that of FastTrack, and that SimpleLock+ generates the lowest overhead among the hybrid detection techniques (Acculock, SimpleLock+, and Multilock-HB) for all benchmark programs. SimpleLock+ is 1.2 times slower than FastTrack on average, but misses one true data race reported from Mutilock-HB on the large-scale benchmark programs.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.75-82
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• 2014

MANET has various types of attacks. In particular, routing attacks using characteristics of movement of nodes and wireless communication is the most threatening because all nodes which configure network perform a function of router which forwards packets. Therefore, mechanisms that detect routing attacks and defense must be applied. In this paper, we proposed hierarchical structure attack detection techniques in order to improve the detection ability against routing attacks. Black hole detection is performed using PIT for monitoring about control packets within cluster and packet information management on the cluster head. Flooding attack prevention is performed using cooperation-based distributed detection technique by member nodes. For this, member node uses NTT for information management of neighbor nodes and threshold whether attack or not receives from cluster head. The performance of attack detection could be further improved by calculating at regular intervals threshold considering the total traffic within cluster in the cluster head.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2004년도 추계 종합학술대회 논문집
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• pp.166-169
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• 2004

변화탐지는 과세에서 군사분야에 이르기까지 많은 응용분야 사용되고 있다. 일반적으로 저해상도 영상에서는 화소차나 화소비와 같은 전체적인 변화탐지 방법이 사용되고 있으며, 고해상도 분야에서는 floating 윈도우 등의 도구를 이용해서 벡터를 입력할 수 있는 국소적인 변화탐지 방법이 사용되고 있다. 그러나 실제적인 사용을 위해서는 변화지역을 자동으로 추출해내는 방법이 연구되어야 할 필요가 있다. 본 연구에서는 변화탐지 모니터링에 사용될 Kompsat 영상의 특징을 알아보고 해상도별 변화탐지 방법에 Kompsat 영상을 활용하여 그 결과를 비교하였다.

• 전력전자학회논문지
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• 제8권2호
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• pp.199-210
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• 2003

본 논문에서는 계통연계형 태양광발전시스템의 고립운전방지를 위한 새로운 고리운전 검출기법을 연구한다. 이를 위하여 계통연계형 태양광발전시스템 및 고립운전시의 특성에 대하여 기술하였다. 또한 고립운전의 검출특성을 향상시키기 위한 새로운 검출기법을 제시하고 해석하였으며 검출시험을 위한 부하조건 선정을 위한 부하임피던스 곡선을 해석적으로 유포하였다 ACSL 시뮬레이션 및 실험을 통하여 제시한 고립운전 검출기법 및 해석결과를 검증하였다.

• Journal of Power Electronics
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• 제15권6호
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• pp.1664-1672
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• 2015

This paper proposes a series arc fault detection algorithm which incorporates peak voltage and harmonic current detectors for single-phase boost power factor correction (PFC) rectifiers. The series arc fault model is also proposed to analyze the phenomenon of the arc fault and detection algorithm. For arc detection, the virtual dq transformation is utilized to detect the peak input voltage. In addition, multiple combinations of low- and high-pass filters are applied to extract the specific harmonic components which show the characteristics of the series arc fault conditions. The proposed model and the arc detection method are experimentally verified through a boost PFC rectifier prototype operating under the grid-tied condition with an artificial arc generator manufactured under the guidelines for the Underwriters Laboratories (UL) 1699 standard.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1272-1275
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• 2002

Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes' decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method was tested in the context of robustness, and the results confirmed the superiority of the proposed technique over conventional correlation-based detection method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.5159-5178
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• 2018

Network Intrusion detection is a rapidly growing field of information security due to its importance for modern IT infrastructure. Many supervised and unsupervised learning techniques have been devised by researchers from discipline of machine learning and data mining to achieve reliable detection of anomalies. In this paper, a deep convolutional neural network (DCNN) based intrusion detection system (IDS) is proposed, implemented and analyzed. Deep CNN core of proposed IDS is fine-tuned using Randomized search over configuration space. Proposed system is trained and tested on NSLKDD training and testing datasets using GPU. Performance comparisons of proposed DCNN model are provided with other classifiers using well-known metrics including Receiver operating characteristics (RoC) curve, Area under RoC curve (AuC), accuracy, precision-recall curve and mean average precision (mAP). The experimental results of proposed DCNN based IDS shows promising results for real world application in anomaly detection systems.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.404-406
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• 2013

영상 에지는 물체 검출, 물체 인식 등의 여러 분야에서 전처리 과정으로 활용되고 있다. 기존의 에지 검출 방법에는 Sobel, Prewitt, Roberts, Laplacian 연산자 등이 있다. 기존의 에지 검출 방법들은 구현이 간단하나 임펄스 잡음 영역에서 에지 검출 특성이 미흡하다. 따라서 기존의 에지 검출 방법들의 단점을 보완하기 위하여, 본 논문에서는 변형된 마스크를 이용한 에지 검출 알고리즘을 제안하였다.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.644-660
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• 2016

The real-time detection of malware remains an open issue, since most of the existing approaches for malware categorization focus on improving the accuracy rather than the detection time. Therefore, finding a proper balance between these two characteristics is very important, especially for such sensitive systems. In this paper, we present a fast portable executable (PE) malware detection system, which is based on the analysis of the set of Application Programming Interfaces (APIs) called by a program and some technical PE features (TPFs). We used an efficient feature selection method, which first selects the most relevant APIs and TPFs using the chi-square ($KHI^2$) measure, and then the Phi (${\varphi}$) coefficient was used to classify the features in different subsets, based on their relevance. We evaluated our method using different classifiers trained on different combinations of feature subsets. We obtained very satisfying results with more than 98% accuracy. Our system is adequate for real-time detection since it is able to categorize a file (Malware or Benign) in 0.09 seconds.

• The Plant Pathology Journal
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• 제34권2호
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• pp.85-92
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• 2018

Enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), widely used for the detection of plant viruses, are not easily performed, resulting in a demand for an innovative and more efficient diagnostic method. This paper summarizes the characteristics and research trends of biosensors focusing on the physicochemical properties of both interface elements and bioconjugates. In particular, the topological and photophysical properties of quantum dots (QDs) are discussed, along with QD-based biosensors and their practical applications. The QD-based Fluorescence Resonance Energy Transfer (FRET) genosensor, most widely used in the biomolecule detection fields, and QD-based nanosensor for Rev-RRE interaction assay are presented as examples. In recent years, QD-based biosensors have emerged as a new class of sensor and are expected to open opportunities in plant virus detection, but as yet there have been very few practical applications (Table 3). In this article, the details of those cases and their significance for the future of plant virus detection will be discussed.