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检索条件"主题词=detection Algorithms"

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detection of DoS and DDoS attacks in NGMN using frequency domain analysis

Detection of DoS and DDoS attacks in NGMN using frequency do...

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Asia-Pacific Conference on Communications

作者： Fazirulhisyam Hashim M. Rubaiyat Kibria Abbas Jamalipour University of Sydney NSW Australia

Ensuring security of the infrastructure against external attacks across network boundaries constitutes one of primary attributes as well as challenges of the next generation mobile network (NGMN). To allay the possibility of such attacks emancipating the NGMN architecture, it is necessary to identify the attack types. However, detection of the attack types from various traffic flows (as is the case in network links) and their subsequent classification can be a very daunting task, especially when both the attack and the legitimate traffic exhibit similar statistical properties (such as denial-of-service (DoS) and distributed DoS (DDoS)). Furthermore, the attackerpsilas ability to spoof and forge the packet header information (including IP address) makes the detection process even more difficult. Conventional anomaly based attack detection mechanisms have been found wanting in such situations. In an attempt to provide a solution, this paper proposes a detection algorithm that identifies and characterizes network traffic by investigating the frequency spectrum distribution. The Lomb periodogram is utilized to determine the power spectrum of the observed traffic whereupon two deviation score parameters are employed to segregate the anomaly traffic flows from legitimate ones in a two-step method. For simplicity purposes, the efficiency of such classification effort is demonstrated for DoS and DDoS attacks only (for their statistical similarity to normal traffic).

关键词： Computer crime Frequency domain analysis Telecommunication traffic Data security Australia Intrusion detection Next generation networking Monitoring detection algorithms Distributed databases

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Knee Point detection on Bayesian Information Criterion

Knee Point Detection on Bayesian Information Criterion

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Qinpei Zhao Mantao Xu Pasi Fränti Speech & Image Processing Unit Department of Computer Science University of Joensuu Joensuu Finland

The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bayesian information criterion (BIC) often serves as a statistical criterion for model selection, which can also be used in solving model-based clustering problems, in particular for determining the number of clusters. Conventionally, a correct number of clusters can be identified as the first decisive local maximum of BIC; however, this is intractable due to the overtraining problem and inefficiency of clustering algorithms. To circumvent this limitation, we proposed a novel method for identifying the number of clusters by detecting the knee point of the resulting BIC curve instead. Experiments demonstrated that the proposed method is able to detect the correct number of clusters more robustly and accurately than the conventional approach.

关键词： Knee Bayesian methods Clustering algorithms detection algorithms Speech analysis Parameter estimation Artificial intelligence Speech processing Image processing Computer science

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Parallel detection algorithm using multiple QR decompositions with permuted channel matrix for SDM/OFDM

Parallel detection algorithm using multiple QR decomposition...

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International Symposium on Wireless Pervasive Computing (ISWPC)

作者： Chang-Jun Ahn Faculty of Information Sciences Hiroshima City University Hiroshima Japan

SDM/OFDM systems transmit different data using the same frequency, so it is necessary to separate simultaneously received signals in the receiver. Previous studies have shown that maximum likelihood detection (MLD) provides the best BER performance. However, the complexity of MLD exponentially increases with the constellation size and the number of transmit antenna branches. Therefore, it is impractical to use a full MLD without reducing its computational complexity, because it would be prohibitively large for implementation. Recently, the use of QRD-M has been proposed for reducing the system complexity, while maintaining the performance of the system. However, the QRD-M performance depends on the number of surviving symbol replica candidates. When QRD-M is used with a small number of surviving symbol replica candidates, the performance declines, but when there is a large number of surviving symbol replica candidates and the transmitter antenna branches, QRD-M requires a large memory to maintain their branch metrics, and long latency time is also required. To reduce these problems, in this paper, we propose a parallel detection algorithm using multiple QR decompositions with permuted channel matrices for SDM/OFDM systems.

关键词： detection algorithms Matrix decomposition OFDM Transmitting antennas Transmitters Receiving antennas Antennas and propagation Maximum likelihood detection Bit error rate Computational complexity

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Anomaly detection in multi-polarimetric radar images

Anomaly detection in multi-polarimetric radar images

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： Georgy Melamed Stanley R. Rotman Dan G. Blumberg Anthony J. Weiss Department Electrical Engineering Tel-Aviv University Israel Department Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel Department Geography and Environmental Development Ben-Gurion University of the Negev Beersheba Israel

An anomaly detection algorithm for SAR (synthetic aperture radar) images, making use of multi-polarized data, is developed. The processing contains several stages including: calibration of the images, information parameters extraction and speckle filtering, suspect pixels detection and morphology operator application. The developed algorithm is independent of the anomaly radar cross section; it depends only on the physical structure. The proposed processing is non-iterative, adaptive and automatic. Performance evaluation shows improved performance of the algorithm over the common alternatives.

关键词： Radar detection Radar imaging detection algorithms Synthetic aperture radar Calibration Parameter extraction Speckle Information filtering Information filters Pixel

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Community detection in Social Networks Employing Component Independency

Community Detection in Social Networks Employing Component I...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zhongmin Xiong Wei Wang Dongmei Huang Department of Computing and Information Technology Fudan University Shanghai China School of Information Shanghai Ocean University Shanghai China

Many networks, including social and biological networks, are naturally divided into communities. Community detection is an important task for the discovering underlying structure in networks. GN algorithm is one of the most influential detection algorithms based on betweenness scores of edges, but it is computationally costly, as all betweenness scores should be repeatedly computed once an edge is removed. Here, an algorithm is presented, which is also based on betweenness scores but more than one edge can be removed when all betweenness scores have been computed. This method is motivated by the consideration: many components, divided from networks, are independent each other in their recalculation of betweenness scores and their split into smaller components. It is shown that this method is fast and effective through theoretical analysis and experiments with several real data sets, which have been acted as test beds in many related works.

关键词： Social network services Biology computing Clustering algorithms Telecommunication traffic Fuzzy systems Computer networks Information technology Oceans detection algorithms Independent component analysis

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A Low Complex V-BLAST detection Algorithm for MIMO-OFDM System

A Low Complex V-BLAST Detection Algorithm for MIMO-OFDM Syst...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Wang Bei Qi Zhu Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing P.R.China

ML-DFE algorithm is known as the combination of the ZF-DFE algorithm and ML algorithm. In this paper, OSIC-ML is proposed as the simplified algorithm of the ML-DFE, by exchanging the executive order of OSIC and ML, using simple matrix operations to replace the method of through QR decomposition to find a unitary matrix for matrix resolution. ML-DFE algorithm decreases complexity of the matrix operations, and gets almost the same performance of ML-DFE algorithm by the Matlab simulation results.

关键词： detection algorithms Matrix decomposition Signal detection MIMO Diversity reception Transmitting antennas Wireless communication Laboratories OFDM Mathematical model

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A study of detection algorithm for DAA regulation of Korea using MB-OFDM UWB receiver

A study of detection algorithm for DAA regulation of Korea u...

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International SoC Design Conference, ISOCC

作者： Cheol-Ho Shin ByoungHak Kim Sangsung Choi Digital Home Research Division Electronics and Telecommunications Research Institute Daejeon South Korea

ISBN: (纸本)9781424425983

This paper analyzed the performance of a detection algorithm using MB-OFDM UWB receiver based on silent time when the victim signal is received by detection limit of -80 dBm/MHz proposed in Korea for DAA. Simulation results show that the performance of the proposed detection algorithm is enough to detect the victim signal with 95% detection probability within the +/-0.5 dB error range if repeat Number over 4 is used.

关键词： detection algorithms FCC OFDM Radio spectrum management Algorithm design and analysis RF signals Baseband Personal area networks Signal analysis Performance analysis

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Dark line detection with line width extraction

Dark line detection with line width extraction

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IEEE International Conference on Image Processing

作者： Qin Li Lei Zhang Jane You David Zhang Prabir Bhattacharya Department of Computing The Hong Kong Polytechnic University Hong Kong Hong Kong China Institute for Information Systems Engineering Concordia University Quebec Canada

Automated line detection is a classical image processing topic with many applications such as road detection in remote images and vessel detection in medical images. Many traditional line detectors, such as Gabor filter, the second order derivative of Gaussian and Radon transform will response not only to lines but also to edges, e.g. they will give high responses to the edges of bright lines or blobs when only dark lines are required. To reduce false detections when extracting only dark (or bright) lines, in this paper we propose a line detector by using the first derivative of Gaussian. It can detect dark lines without much false detection on blobs or bright lines. Meanwhile, the proposed method can estimate line width simultaneously. Experiments on various images are performed to test the proposed algorithm.

关键词： Image edge detection Detectors detection algorithms Gabor filters Band pass filters Roads Biomedical imaging Data mining Information systems Systems engineering and theory

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A Parallel Approach for Initialization of High-Order Statistics Anomaly detection in Hyperspectral Imagery

A Parallel Approach for Initialization of High-Order Statist...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Hsuan Ren Yang-Lang Chang Center for Space and Remote Sensing Research National Central University Chungli Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan

Anomaly detection for remote sensing has drawn a lot of attention lately. An anomaly has distinct spectral features from its neighborhood, whose spectral signature is not known a priori, and it usually has small size with only a few pixels. It is very challenge to detect anomalies, especially without any information of the background environment in hyperspectral data with hundreds of co-registered image bands. Several methods are devoted to this problem, including the well-known RX algorithm which takes advantage of the second-order statistics and other algorithms which detect anomaly based on higher order statistics such as skewness and kurtosis. It has been proved that the High-Order Automatic Anomaly detection Algorithm can outperform RX algorithm by distinguishing different types of anomalies. However, the initialization of the High-Order Automatic Anomaly detection Algorithm remains a challenge problem. When the initial vectors are selected randomly for this recursive algorithm, they might be trapped in the local maximums and give different projection directions. But in our experiments, all those directions will show different types of anomalies. Therefore, this algorithm is particular suitable for parallel processing to increase the computing efficiency. In the parallel architecture, we will first randomly generate initial vectors for each process, and then united those output results for the orthogonal projection base. We will also compare the computational efficiency with the number of parallel processes we used.

关键词： Hyperspectral imaging Higher order statistics Hyperspectral sensors Clustering algorithms Space technology Remote sensing detection algorithms Concurrent computing Parallel processing Parallel architectures

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detection of line defects in steel billets using undecimated wavelet transform

Detection of line defects in steel billets using undecimated...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Jong Pil Yun SungHoo Choi Yong-ju Jeon Doo-chul Choi Sang Woo Kim Department of Electronic and Electrical Engineering POSTECH Pohang South Korea

In this paper, we present a new detection algorithm for line defects of scale-covered steel billets. Because of the presence of scales on the billet surface, features of surface images such as brightness and textures are non-uniform. To minimize the influence of scales and to improve the accuracy of detection, a new detection method based on undecimated wavelet transform is proposed. The vertical projection profile of subimage with high-frequency information produced by undecimated wavelet transform is used to detect the line defects. Experimental results conducted on billets surface image from actual steel production line show that the proposed algorithm is capable of detecting line defects on billet surface.

关键词： Steel Billets Wavelet transforms Surface morphology Inspection Welding detection algorithms Image edge detection Filters Pixel

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