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检索条件"主题词=Change Detection Algorithms"

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Dynamic model selection with its applications to computer security

Dynamic model selection with its applications to computer se...

引用

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Y. Maruyama K. Yamanishi NEC Corporation Limited Kawasaki Kanagawa Japan

In recent years there has been increased interest in detecting anomalies in network traffic data/audit logs for computer security. With the appearance of a masquerader, for example, any new anomalous behavior pattern may be observed in command line data, and it is an important issue to detect the emergence of such a pattern as early as possible. This paper addresses this issue of anomaly detection by dynamically selecting statistical models from data. Our goal is here not to select a single model over the data as in conventional statistical model selection, but to select a time series of optimal models efficiently, assuming that the true model may change over time. We call this approach dynamic model selection. We first propose a coding-theoretic criterion for dynamic model selection. Next, we propose two dynamic model selection algorithms attaining the minimum of the criteria and analyze their performance. Finally we demonstrate the validity of our algorithms through real application to masquerade detection using UNIX command sequences.

关键词： Application software Computer security Intrusion detection National electric code Telecommunication traffic change detection algorithms Electronic mail Traffic control Performance analysis Algorithm design and analysis

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Binary Document Images Authentication by Thinning Digital Patterns

Binary Document Images Authentication by Thinning Digital Pa...

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Chu-Hsing Lin Wen-Kui Chang Yu-Ying Lin Lun-Yuen Cheng Department of Computer Science and Information Engineering Tunghai University Taichung Taiwan

ISBN: (纸本)9780769529943;0769529941

As most documents have been digitized and transmitted over the Internet, it becomes very crucial to protect the integrity of them. Integrity is the process of ensuring that a document is changed by unauthorized users. In this paper, inspired by the Yang and Kot's method, we proposed a novel scheme to verify the integrity of binary documents by using its digital patterns. We compute the black patterns and white patterns of a document and embed watermark information in it. The experimental result shows that by using our proposed method one can verify the integrity of a digital document, any little change made to it can be detected easily.

关键词： Authentication Watermarking Protection Internet Embedded computing Handheld computers Cryptography Payloads Computer science change detection algorithms

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detection of Low Intensity DoS Attacks using Fuzzy Based Intrusion detection System

Detection of Low Intensity DoS Attacks using Fuzzy Based Int...

引用

International Conference on Electrical and Computer Engineering (ICECE)

作者： Habibullah Baig Farrukh Kamran Center for Advanced Studies in Engineering Pakistan

Detecting low intensity denial of service (DoS) attacks in minimum time with less false positives is challenging for network based intrusion detection systems. In this paper we propose a new fuzzy logic based approach, which adapts fuzzy linguistic membership functions instead of modifying the fuzzy rules. The authors use the normal TCP profile, i.e. the `connected-sessions', to guide the fuzzy membership set boundaries. The authors also propose implementation architecture with a hierarchy of fuzzy agents responsible for detecting different types of attacks. This scheme reduces the number of false alarms at lower level of hierarchy. Tests have been conducted and are reported using DARPA98 datasets

关键词： Computer crime Fuzzy systems Intrusion detection Fuzzy logic Telecommunication traffic Traffic control change detection algorithms Data mining Random variables Probability

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Imprecisions Diagnostic in Source Code Deltas

Imprecisions Diagnostic in Source Code Deltas

引用

International Mining Software Repositories, MSR

作者： Guillermo de la Torre Romain Robbes Alexandre Bergel DCC University of Chile Santiago Chile SwSE Research Group Free University of Bozen-Bolzano Bolzano Italy

Beyond a practical use in code review, source code change detection (SCCD) is an important component of many mining software repositories (MSR) approaches. As such, any error or imprecision in the detection may result in a wrong conclusion while mining repositories. We identified, analyzed, and characterized impressions in GumTree, which is the most advanced algorithm for SCCD. After analyzing its detection accuracy over a curated corpus of 107 C# projects, we diagnosed several imprecisions. Many of our findings confirm that a more language-aware perspective of GumTree can be helpful in reporting more precise changes.

关键词： Software Data mining Transforms C# languages Syntactics change detection algorithms Software algorithms

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Three-dimensional indoor localization in Non Line of Sight UWB channels

Three-dimensional indoor localization in Non Line of Sight U...

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IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Jens Schroeder Stefan Galler Kyandoghere Kyamakya Thomas Kaiser Institute of Communications Engineering (IKT) Leibniz University Hannover Germany Institute for Smart System-Technologies Alpen-Adria University of Klagenfurt Austria

The problem of indoor localization is lately gaining high interest in research and industry. In this context, Ultra-Wideband has the capability of fulfilling the task of precise localization. Non Line of Sight (NLOS) channels, however, can seriously degrade the positioning accuracy. This paper gives a contribution to the frequent case, where base station redundancy in a three-dimensional localization system in time-of-arrival (TOA) configuration is not available. Literature analysis shows that many existing NLOS mitigation algorithms cannot be applied in such a case. Therefore, an algorithm using geometrical projection is proposed in comparison to Kalman filtered range estimates. Both algorithms rely on NLOS detection, which is implemented using the change of SNR method. Finally, the algorithms are tested in a laboratory room using an UWB localization test bed.

关键词： Base stations change detection algorithms Ultra wideband technology Testing Redundancy Indoor environments Communication industry Context Degradation Laboratories

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Multi-Scale Rank-Permutation change Localization

Multi-Scale Rank-Permutation Change Localization

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IEEE Conference on Aerospace

作者： Neil H. W. Eklund Xiao Hu One Research Circle General Electric Global Research Schenectady NY USA

Prediction of equipment remaining useful life (RUL) is of considerable economic benefit to industry, by permitting the avoidance of unscheduled downtime and costly secondary damage. detection of change is an important first step in building a prognostic system: when a detectable fault occurs, it will cause changes in one or more sensed parameters of the system. Once a change has been detected, localizing the time of change (presumably the time of fault onset), can contribute to the estimate of RUL in two ways. First, it may make the RUL estimate more accurate. Second, and independent of estimate accuracy, it may make the prognostic estimate more precise by reducing the variance of the estimate. This paper describes an approach for localizing the time of change in time series data. The performance of the system is assessed using synthetic data that closely matches the characteristics of real-world data. However, the synthetic data is deterministically labeled, so algorithm performance can accurately be assessed. The approach presented requires low computational power at runtime, an important feature for on-wing application that combines the rank transformation of data, randomization tests inspired by the work of Fisher and Pitman, and fusion of multi-scale estimates to result in a fast and accurate localization of change.

关键词： Fault detection Signal processing algorithms Costs change detection algorithms Power generation economics Equipment failure detection algorithms Logic testing Sequential analysis Delay

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Spatio-temporal joint probability images for video segmentation

Spatio-temporal joint probability images for video segmentat...

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IEEE International Conference on Image Processing

作者： Ze-Nian Li Jie Wei School of Computing Science Simon Fraser University Burnaby Canada Department of Computer Science City College City University of New York New York NY USA

ISBN: (纸本)0780362977

In this paper we propose a novel video segmentation algorithm that is capable of reliably detecting both types of dissolves in addition to cuts and wipes based on the analysis of the spatio-temporal behavior of joint probability images (JPIs). Experimental results for identifying scene transitions in various video clips that contain moderate and significant amounts of movements are demonstrated.

关键词： Image segmentation Layout Cities and towns Image edge detection Histograms Computer science Educational institutions Indexing Motion detection change detection algorithms

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Robust abnormity detecting and tracking using correlation coefficient

Robust abnormity detecting and tracking using correlation co...

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International Conference on Multimedia Modeling (MMM)

作者： Jin Zheng Bo Li Chunlian Yao Digital Media Laboratory School of Computer Science and Engineerinlg Beihang University Beijing China

Abnormity detection based on computer vision is the foundation of high-level automatic surveillance that includes objects recognition, tracking and alarm etc. In this paper, a robust abnormity detection algorithm using improved correlation coefficient is proposed. It assembles every pixel and its neighboring pixels to form a vector, and computes correlation coefficient to measure the similarity of corresponding window in the background image and current image. When the correlation coefficient is bigger than the adaptive threshold, the algorithm processes pixel level detection. Moreover, using k-means and correlation coefficient respectively, it realizes the clustering and tracking of the abnormity objects. The experimental results show the algorithm is robust against noise disturbance, illumination change, shadows and reflection effect. It can detect abnormity precisely, and improve the surveillance system's adaptability for the complicated environment greatly

关键词： Robustness Surveillance Pixel change detection algorithms Clustering algorithms Object detection Computer vision Object recognition detection algorithms Assembly

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Segmentation of fractal network traffic with wavelets and log-likelihood statistics

Segmentation of fractal network traffic with wavelets and lo...

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IEEE International Conference on Communications (ICC)

作者： D. Rincon S. Sallent Escola Politècnica Superior de Castelldefels Universitat Politècnica de Catalunya (UPC) Barcelona Spain

Network traffic exhibits long-range dependence (LRD). The estimators of LRD parameters based on the discrete wavelet transform (DWT) are the best in terms of efficiency and accuracy. These estimators do not consider non-stationarity or changes in the LRD parameters. We propose using the Schwarz information criterion (SIC) to detect changes in the variance structure of the wavelet decomposition, and segmenting the traffic into pieces with homogeneous characteristics for the Hurst parameter. The procedure can be extended to the stationary wavelet transform (SWT), a non-orthogonal transform that provides higher accuracy in the estimation of the change points. The SIC analysis can be performed on-line (in the sense of progressively). The algorithm has been tested against synthetic and real traffic traces with promising preliminary results.

关键词： Fractals Telecommunication traffic Statistics Discrete wavelet transforms Silicon carbide change detection algorithms Traffic control Multiresolution analysis Wavelet transforms Parameter estimation

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Video Segmentation with Model-Based Sprite Generation for Panning Surveillance Cameras

Video Segmentation with Model-Based Sprite Generation for Pa...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Der-Chun Cherng Shao-Yi Chien Media IC and System Lab Graduate Institute of Electronics Engineering and Department of Electrical Engineering National Taiwan University Taipei Taiwan

Video segmentation is one of the most important techniques for advanced video surveillance systems. Most of the existing video segmentation algorithms suffer from high computational complexity to achieve acceptable results for surveillance systems and cannot deal with moving camera situations. In this paper, we propose a low complexity video segmentation algorithm with model-based sprite generation for panning cameras. The characteristics of surveillance systems are utilized to reduce the complexity of sprite generation, which is employed to register background information for panning cameras. In addition, several novel techniques are also proposed to improve the quality of segmentation results. Experimental results show that the proposed algorithm can effectively segment moving objects with good subjective quality.

关键词： Sprites (computer) Surveillance Cameras Image segmentation change detection algorithms Motion estimation Integrated circuit modeling Computational complexity Object segmentation Object detection

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