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real-valued multi-area self set optimization in immunity-based network intrusion detection system

High Technology Letters 2012年第1期18卷 1-6页

作者： Zhang Fengbin Xi Liang Wang Shengwen College of Computer Science and Technology Harbin University of Science and TechnologyHarbin 150080P.R.China

The real-valued self set in immunity-based network intrusion detection system （INIDS） has some defects： multi-area and overlapping, which are ignored before. The detectors generated by this kind of self set may have the problem of boundary holes between self and nonself regions, and the generation efficiency is low, so that, the self set needs to be optimized before generation stage. This paper proposes a self set optimization algorithm which uses the modified clustering algorithm and Gaussian distribution theory. The clustering deals with multi-area and the Gaussian distribution deals with the overlapping. The algorithm was tested by Iris data and real network data, and the results show that the optimized self set can solve the problem of boundary holes, increase the efficiency of detector generation effectively, and improve the system＇s detection rate.

关键词： immunity-based network intrusion detection system (NIDS) real-valued self set optimization

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Image Encryption Algorithm Based on Compressive Sensing and Fractional DCT via Polynomial Interpolation

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International Journal of Automation and computing 2020年第2期17卷 292-304页

作者： Ya-Ru Liang Zhi-Yong Xiao School of Engineering Jiangxi Agricultural UniversityNanchang 330045China School of Software Jiangxi Agricultural UniversityNanchang 330045China

Based on compressive sensing and fractional discrete cosine transform(DCT)via polynomial interpolation(PI-FrDCT),an image encryption algorithm is proposed,in which the compression and encryption of an image are accomplished *** can keep information secret more effectively with low data ***-dimensional piecewise and nonlinear chaotic maps are employed to obtain a generating sequence and the exclusive OR(XOR)matrix,which greatly enlarge the key space of the encryption *** many other fractional transforms,the output of PI-FrDCT is real,which facilitates the storage,transmission and display of the encrypted *** to the introduction of a plain-image-dependent disturbance factor,the initial values and system parameters of the encryption scheme are determined by cipher keys and ***,the proposed encryption scheme is very sensitive to the plain-image,which makes the encryption system more *** results demonstrate the validity and the reliability of the proposed encryption algorithm.

关键词： Compressive sensing fractional discrete cosine transform(DCT)via polynomial interpolation image encryption threedimensional piecewise and nonlinear chaotic maps real-valued output

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Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis

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Journal of Intelligent Learning Systems and Applications 2013年第1期5卷 48-56页

作者： Rongshuai Li Akira Mita Jin Zhou Department of System Design Engineering Keio University Yokohama Japan.

This hybrid methodology for structural health monitoring (SHM) is based on immune algorithms (IAs) and symbolic time series analysis (STSA). real-valued negative selection (RNS) is used to detect damage detection and adaptive immune clonal selection algorithm (AICSA) is used to localize and quantify the damage. Data symbolization by using STSA alleviates the effects of harmful noise in raw acceleration data. This paper explains the mathematical basis of STSA and the procedure of the hybrid methodology. It also describes the results of an simulation experiment on a five-story shear frame structure that indicated the hybrid strategy can efficiently and precisely detect, localize and quantify damage to civil engineering structures in the presence of measurement noise.

关键词： Structural Health Monitoring Adaptive Immune Clonal Selection Algorithm Symbolic Time Series Analysis real-valued Negative Selection Building Structures

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Linear Prolate Functions for Signal Extrapolation with Time Shift

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Applied Mathematics 2017年第4期8卷 417-427页

作者： Daniela Valente Michael Cada Jacek Ilow Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

We propose a low complexity iterative algorithm for band limited signal extrapolation. The extrapolation method is based on the decomposition of finite segments of the signal via truncated series of real-valued linear prolate functions. Our theoretical derivation shows that given a truncated series (up to a selectable value) of prolate functions, it is possible to extrapolate the band limited function elsewhere if each extrapolated portion of the function is subject only to moderate truncation errors that we quantify in this paper. The effects of different sources of errors have been analyzed via extensive simulations. We have investigated a property of the signal decomposition formula based on linear prolate functions whereby the integration interval does not need to be symmetric with respect to the origin while time-shifted prolate functions are used in the series.

关键词： real-valued Band Limited Eigenvectors Signal Decomposition Signal Extrapolation

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