The Experts below are selected from a list of 15690 Experts worldwide ranked by ideXlab platform
Yang Xiang - One of the best experts on this subject based on the ideXlab platform.
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Resisting Web Proxy-Based HTTP Attacks by Temporal and Spatial Locality Behavior
2013Co-Authors: Yi Xie, Shensheng Tang, Yang XiangAbstract:A novel server-side defense scheme is proposed to resist the Web proxy-based distributed denial of service attack. The approach utilizes the temporal and Spatial Locality to extract the behavior features of the proxy-to-server traffic, which makes the scheme independent of the traffic intensity and frequently varying Web contents. A nonlinear mapping function is introduced to protect weak signals from the interference of infrequent large values. Then, a new hidden semi-Markov model parameterized by Gaussian-mixture and Gamma distributions is proposed to describe the time-varying traffic behavior of Web proxies. The new method reduces the number of parameters to be estimated, and can characterize the dynamic evolution of the proxy-to-server traffic rather than the static statistics. Two diagnosis approaches at different scales are introduced to meet the requirement of both fine-grained and coarse-grained detection. Soft control is a novel attack response method proposed in this work. It converts a suspicious traffic into a relatively normal one by behavior reshaping rather than rudely discarding. This measure can protect the quality of services of legitimate users. The experiments confirm the effectiveness of the proposed scheme.
Yi Xie - One of the best experts on this subject based on the ideXlab platform.
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Resisting Web Proxy-Based HTTP Attacks by Temporal and Spatial Locality Behavior
2013Co-Authors: Yi Xie, Shensheng Tang, Yang XiangAbstract:A novel server-side defense scheme is proposed to resist the Web proxy-based distributed denial of service attack. The approach utilizes the temporal and Spatial Locality to extract the behavior features of the proxy-to-server traffic, which makes the scheme independent of the traffic intensity and frequently varying Web contents. A nonlinear mapping function is introduced to protect weak signals from the interference of infrequent large values. Then, a new hidden semi-Markov model parameterized by Gaussian-mixture and Gamma distributions is proposed to describe the time-varying traffic behavior of Web proxies. The new method reduces the number of parameters to be estimated, and can characterize the dynamic evolution of the proxy-to-server traffic rather than the static statistics. Two diagnosis approaches at different scales are introduced to meet the requirement of both fine-grained and coarse-grained detection. Soft control is a novel attack response method proposed in this work. It converts a suspicious traffic into a relatively normal one by behavior reshaping rather than rudely discarding. This measure can protect the quality of services of legitimate users. The experiments confirm the effectiveness of the proposed scheme.
Li-zhi Fang - One of the best experts on this subject based on the ideXlab platform.
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Spatial Locality of Galaxy Correlation Function in Phase Space: Samples from the 2MASS Extended Source Catalog
2004Co-Authors: Yicheng Guo, Yaoquan Chu, Li-zhi FangAbstract:We analyze the statistical properties and dynamical implications of galaxy distributions in phase space for samples selected from the 2MASS extended source catalog. The galaxy distribution is decomposed into modes δ(k,x), which describe the number density perturbations of galaxies in a phase-space cell given by scale band k to k + Δk and Spatial range x to x + Δx. In the nonlinear regime, δ(k,x) is highly non-Gaussian. We find, however, that the correlations between δ(k,x) and δ(k',x') are always very weak if the Spatial ranges (x, x + Δx) and (x', x' + Δx') do not overlap. This feature is due to the fact that the Spatial Locality of the initial perturbations is "memorized" during hierarchical clustering. The highly Spatial Locality of the 2MASS galaxy correlations is strong evidence for the initial perturbations of the cosmic mass field being Spatially localized and is therefore consistent with Gaussian initial perturbations on scales as small as about 0.1 h-1 Mpc. Moreover, the 2MASS galaxy Spatial Locality indicates that the relationship between density perturbations of galaxies and the underlying dark matter should be localized in phase space. That is, for a structure consisting of perturbations on scales from k to k + Δk, the nonlocal range in the relation between galaxies and dark matter should not be larger than |Δx| = 2π/|Δk|. The stochasticity and nonLocality of the bias relation between galaxies and dark matter fields should be no more than the allowed range given by the uncertainty relation |Δx||Δk| = 2π.
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Spatial Locality of galaxy correlation function in phase space samples from the 2mass extended source catalog
2004Co-Authors: Yicheng Guo, Yaoquan Chu, Li-zhi FangAbstract:We analyze the statistical properties and dynamical implications of galaxy distributions in phase space for samples selected from the 2MASS Extended Source Catalog. The galaxy distribution is decomposed into modes $\delta({\bf k, x})$ which describe the number density perturbations of galaxies in phase space cell given by scale band $\bf k$ to ${\bf k}+\Delta {\bf k}$ and Spatial range $\bf x$ to ${\bf x}+\Delta {\bf x}$. In the nonlinear regime, $\delta({\bf k, x})$ is highly non-Gaussian. We find, however, that the correlations between $\delta({\bf k, x})$ and $\delta({\bf k', x'})$ are always very weak if the Spatial ranges (${\bf x}$, ${\bf x}+\Delta {\bf x}$) and (${\bf x'}$, ${\bf x'}+\Delta {\bf x'}$) don't overlap. This feature is due to the fact that the Spatial Locality of the initial perturbations is memorized during hierarchical clustering. The highly Spatial Locality of the 2MASS galaxy correlations is a strong evidence for the initial perturbations of the cosmic mass field being Spatially localized, and therefore, consistent with a Gaussian initial perturbations on scales as small as about 0.1 h$^{-1}$ Mpc. Moreover, the 2MASS galaxy Spatial Locality indicates that the relationship between density perturbations of galaxies and the underlying dark matter should be localized in phase space. That is, for a structure consisting of perturbations on scales from $k$ to $ k+\Delta {k}$, the nonlocal range in the relation between galaxies and dark matter should {\it not} be larger than $|{\Delta {\bf x}}|=2\pi/|\Delta {\bf k}|$. The stochasticity and nonLocality of the bias relation between galaxies and dark matter fields should be no more than the allowed range given by the uncertainty relation $|{\Delta {\bf x}|| \Delta{\bf k}}|=2\pi$.
Shensheng Tang - One of the best experts on this subject based on the ideXlab platform.
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Resisting Web Proxy-Based HTTP Attacks by Temporal and Spatial Locality Behavior
2013Co-Authors: Yi Xie, Shensheng Tang, Yang XiangAbstract:A novel server-side defense scheme is proposed to resist the Web proxy-based distributed denial of service attack. The approach utilizes the temporal and Spatial Locality to extract the behavior features of the proxy-to-server traffic, which makes the scheme independent of the traffic intensity and frequently varying Web contents. A nonlinear mapping function is introduced to protect weak signals from the interference of infrequent large values. Then, a new hidden semi-Markov model parameterized by Gaussian-mixture and Gamma distributions is proposed to describe the time-varying traffic behavior of Web proxies. The new method reduces the number of parameters to be estimated, and can characterize the dynamic evolution of the proxy-to-server traffic rather than the static statistics. Two diagnosis approaches at different scales are introduced to meet the requirement of both fine-grained and coarse-grained detection. Soft control is a novel attack response method proposed in this work. It converts a suspicious traffic into a relatively normal one by behavior reshaping rather than rudely discarding. This measure can protect the quality of services of legitimate users. The experiments confirm the effectiveness of the proposed scheme.
Chenyang Yang - One of the best experts on this subject based on the ideXlab platform.
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Caching at Base Stations With Heterogeneous User Demands and Spatial Locality
2019Co-Authors: Dong Liu, Chenyang YangAbstract:The existing proactive caching policies are designed by assuming that all users request contents with identical activity level at uniformly distributed or known locations, among which most of the policies are optimized by assuming that user preference is identical to content popularity. However, these assumptions are not true based on the recent data analysis. In this paper, we investigate what happens without these assumptions. To this end, we establish a framework to optimize caching policy for base stations exploiting heterogeneous user preference, activity level, and Spatial Locality. We derive success probability and average rate of each user as utility function, respectively, and obtain the optimal caching policy maximizing a weighted sum of average utility (reflecting network performance) and minimal utility of users (reflecting user fairness). To investigate the intertwined impact of individual user request behavior on caching, we provide an algorithm to synthesize user preference from given content popularity and activity level with controlled preference similarity and validate the algorithm with the real datasets. Analysis and simulation results show that exploiting individual user behavior can improve both network performance and user fairness, and the gain increases with the skewness of Spatial Locality, and the heterogeneity of user preference and activity level.
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Optimizing Caching Policy at Base Stations by Exploiting User Preference and Spatial Locality.
2017Co-Authors: Dong Liu, Chenyang YangAbstract:Most prior works of proactive caching at wireless edge optimize caching policies under the following assumptions: the preference of each user is identical to content popularity, all users request contents with the same active level and at uniformly-distributed locations. In this paper, we investigate what happens without these assumptions. To this end, we establish a framework to optimize caching policy at base stations exploiting user preference, active level, and Spatial Locality. We obtain optimal caching policy to minimize the weighted sum of the file download time averaged over all file requests and user locations in the network (reflecting network performance) and the maximal weighted download time averaged over possible file requests and locations of each user (reflecting user fairness). To investigate how user preference similarity and active level skewness affect the optimal caching policy, we then provide a method to synthesize user preference for given content popularity and user active level. The analysis and simulation results show that exploiting user preference can improve both network performance and user fairness remarkably compared with priori works. The gain of exploiting user preference increases with user preference heterogeneity, user Spatial Locality, and skewness of user active level.
