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您的检索式：作者名="Ruomeng Xu"
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| 1 | An Abnormal Network Flow Feature Sequence Prediction Approach for DDoS Attacks Detection in Big Data Environment显示文摘Distributed denial-of-service(DDoS)is a rapidly growing problem with the fast development of the Internet.There are multitude DDoS detection approaches,however,three major problems about DDoS attack detection appear in the big data environment.Firstly,to shorten the respond time of the DDoS attack detector;secondly,to reduce the required compute resources;lastly,to achieve a high detection rate with low false alarm rate.In the paper,we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems.We define a network flow abnormal index as PDRA with the percentage of old IP addresses,the increment of the new IP addresses,the ratio of new IP addresses to the old IP addresses and average accessing rate of each new IP address.We design an IP address database using sequential storage model which has a constant time complexity.The autoregressive integrated moving average(ARIMA)trending prediction module will be started if and only if the number of continuous PDRA sequence value,which all exceed an PDRA abnormal threshold(PAT),reaches a certain preset threshold.And then calculate the probability that is the percentage of forecasting PDRA sequence value which exceed the PAT.Finally we identify the DDoS attack based on the abnormal probability of the forecasting PDRA sequence.Both theorem and experiment show that the method we proposed can effectively reduce the compute resources consumption,identify DDoS attack at its initial stage with higher detection rate and lower false alarm rate. | Jieren Cheng Ruomeng Xu Xiangyan Tang Victor S.Sheng Canting Cai | 2018 | Computers, Materials & Continua2018，，4： | 15 |
| 2 | The compensatory phenomenon of the functional connectome related to pathological biomarkers in individuals with subjective cognitive decline显示文摘Background Subjective cognitive decline(SCD)is a preclinical stage along the Alzheimer’s disease(AD)continuum.However,little is known about the aberrant patterns of connectivity and topological alterations of the brain functional connectome and their diagnostic value in SCD.Methods Resting-state functional magnetic resonance imaging and graph theory analyses were used to investigate the alterations of the functional connectome in 66 SCD individuals and 64 healthy controls(HC).Pearson correlation analysis was computed to assess the relationships among network metrics,neuropsychological performance and pathological biomarkers.Finally,we used the multiple kernel learning-support vector machine(MKL-SVM)to differentiate the SCD and HC individuals.Results SCD individuals showed higher nodal topological properties(including nodal strength,nodal global efficiency and nodal local efficiency)associated with amyloid-βlevels and memory function than the HC,and these regions were mainly located in the default mode network(DMN).Moreover,increased local and medium-range connectivity mainly between the bilateral parahippocampal gyrus(PHG)and other DMN-related regions was found in SCD individuals compared with HC individuals.These aberrant functional network measures exhibited good classification performance in the differentiation of SCD individuals from HC individuals at an accuracy up to 79.23%.Conclusion The findings of this study provide insight into the compensatory mechanism of the functional connectome underlying SCD.The proposed classification method highlights the potential of connectome-based metrics for the identification of the preclinical stage of AD. | Haifeng Chen Xiaoning Sheng Caimei Luo Ruomeng Qin Qing Ye Hui Zhao Yun Xu Feng Bai 无 | 2020 | Translational Neurodegeneration2020，9，2： | 5 |
| 3 | Propagation behavior of SH waves in a piezomagnetic substrate with an orthorhombic piezoelectric layer显示文摘The dispersion behavior of the shear horizontal(SH) waves in the coupled structure consisting of a piezomagnetic substrate and an orthorhombic piezoelectric layer is investigated with different cut orientations. The surface of the piezoelectric layer is mechanically free, electrically shorted, or open, while the surface of the piezomagnetic substrate is mechanically free, magnetically open, or shorted. The dispersion relations are derived for four electromagnetic boundary conditions. The dispersion characteristics are graphically illustrated for the layered structure with the PMN-PT layer perfectly bonded on the CoFe_2O_4 substrate. The effects of the PMN-PT cut orientations, the electromagnetic boundary conditions, and the thickness ratio of the layer to the substrate on the dispersion behavior are analyzed and discussed in detail. The results show that,(i)the effect of the cut orientation on the dispersion curves is very obvious,(ii) the electrical boundary conditions of the PMN-PT layer dominate the propagation feature of the SH waves, and(iii) the thickness ratio has a significant effect on the phase velocity when the wave number is small. The results of the present paper can provide valuable theoretical references to the applications of piezoelectric/piezomagnectic structure in acoustic wave devices. | Yanping KONG Ruomeng TIAN Jie XU Jinxi LIU | 2018 | Applied Mathematics and Mechanics(English Edition)2018，39，2： | 0 |
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