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IGED:Towards intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

Computers, Materials & Continua 2024年第8期80卷 1851-1866页

作者： Yanhua Liu Yuting Han HuiChen Baokang Zhao XiaofengWang Ximeng Liu College of Computer and Data Science Fuzhou UniversityFuzhou350108China Engineering Research Center of Big Data Intelligence Ministry of EducationFuzhou350108China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350108China College of Computer National University of Defense TechnologyChangsha410073China

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data *** the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization *** results show that the proposed method can efficiently distinguish normal traffic from DDoS *** with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

关键词： DDoS real-time improved generalized entropy DNN

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Semi-supervised PolSAR image classification method based on contrastive learning 6

Semi-supervised PolSAR image classification method based on ...

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6th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2023

作者： Hua, Wenqiang Sun, Nan Liu, Lin The Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an Key Laboratory of Big Data and Intelligent Computing School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China School of Computer Technology Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9798400707674

Polarimetric synthetic aperture radar (PolSAR) image classification has important application value and a wide range of application scenarios in many fields. Supervised classification methods, which need to use a large amount of labeled data to improve classification accuracy, have achieved satisfactory classification performance. However, it is difficult and expensive to obtain sufficient labeled data for PolSAR images. The problem to be solved is how to obtain high classification accuracy with a limited number of labeled samples. Semi-supervised PolSAR image classification method based on contrastive learning is proposed. Firstly, a supervised PolSAR image classification method based on meta-learning is introduced. Prototypical network based on meta-learning ideas is used as the basic classification model, and a prototypical representation is created for each category. Classification is performed by computing the similarity between the prototypical representation and samples to be classified. Secondly, a method of training feature extractor based on contrastive learning is designed. By maintaining the consistency of features between the same data and distinguishing the differences between different data after data augmentation, the method enables the feature extractor to obtain accurate feature representation. By co-training with meta-learning, so as to improve the classification performance. Finally, experiments on real PolSAR data prove the effectiveness of the proposed method. © 2023 ACM.

关键词： Image classification

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Assessment and prediction of leakage degree of expansion joints in underground network heating pipe network based on LS-SVM and ARIMA model 13

Assessment and prediction of leakage degree of expansion joi...

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13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

作者： Shang-Bin, Jiao Le, Fan Peng-Yue, Wu Lei, Qiao Yong-Ze, Jin Qian-Kun, Shen Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Xi'an Thermal Power Research Institute Co. Ltd Xi'an710054 China

ISBN: (纸本)9781538637579

The study shows that the leakage of the expansion joints in the underground heating primary pipe network will lead to the fluctuation of soil temperature and conductivity around the leakage point. Based on the online monitoring of changes of physical quantities around the expansion joint, this paper established the assessment model of temperature and conductivity as the input parameters and the degree of expansion joints leakage as the output parameters, which took the radial basis function as kernel function and made use of PSO algorithm to achieve the optimization of the kernel function parameters. Then, the temperature and conductivity were predicted based on the ARIMA model, and the LS-SVM assessment of expansion joint leakage was realized according to the prediction results. Both simulation and field experiments show that the prediction model based on ARIMA has higher accuracy, which has identified the foundation for on-line prediction and accurate assessment of the expansion joint leakage in the underground heating primary pipe network. © 2018 IEEE.

关键词： Particle swarm optimization (PSO)

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Upconversion Circularly Polarized Luminescence with Dissymmetry Factor Up to 1.80 from Flexible Perovskite-Liquid Crystal Membranes

SSRN

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SSRN 2025年

作者： Hu, Xiaowen Pu, Yuyang Wen, Xuebing Gu, Haotian Zhu, Huilong Yuan, Ming Huang, Jiaqi Zhan, Qiuqiang Jiang, Xiao-Fang Polavarapu, Lakshminarayana Zhou, Guofu Guangdong Provincial Key Laboratory of Optical Information Materials and Technology South China Academy of Advanced Optoelectronics South China Normal University Guangzhou510006 China National Center for International Research on Green Optoelectronics South China Normal University Guangzhou510006 China Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter School of Physics South China Normal University Guangzhou510006 China Centre for Optical and Electromagnetic Research Guangdong Engineering Research Centre of Optoelectronic Intelligent Information Perception South China Academy of Advanced Optoelectronics South China Normal University Guangzhou510006 China CINBIO Universidade de Vigo Materials Chemistry and Physics Group Department of Physical Chemistry Campus Universitario Lagoas Marcosende Vigo36310 Spain

Upconversion circularly polarized luminescence (UC-CPL) which refers to the emission of circularly polarized light upon excitation with low-energy photons through photon upconverion process, has garnered significant attention due to its distinctive photonic properties. However, achieving high dissymmetry factors for UC-CPL through a simple thin-film design remains a challenge. Here, a flexible UC-CPL membrane device is reported, consisting of a composite film of upconversion nanoparticles (UCNPs) and perovskite nanocrystals (PNCs) integrated with a cholesteric liquid crystal (CLC) polymer film. The UCNPs and PNCs composite was synthesized via a one-step in-situ method, facilitating efficient nonradiative Förster resonance energy transfer (FRET) from UCNPs to PNCs, as evidenced by the shortened time-resolved fluorescence decay lifetime of the UCNPs. By designing the CLC film with a photonic bandgap that matches the emission peak of the PNCs, a UC-CPL with a dissymmetry factor of 1.8 was achieved. This is attributed to the circular polarization selection characteristics induced by the periodic helical structure of the CLC. The membrane device is fully solution-processable and exhibits ultra-flexibility as the emission intensity remains unchanged after repeated 300 bending cycles. Microscale pattern was inscribed on the membrane using femtosecond laser direct writing (FsLDW), and the pattern, with dual-mode CPL capability, exhibit distinct colors under different excitation wavelengths and reading modes. These findings represent the demonstration of perovskite based UC-CPL from a flexible membrane device with a high [[EQUATION]], providing valuable insights for practical applications for micro/nano-scale optical information encryption and anti-counterfeiting. © 2025, The Authors. All rights reserved.

关键词： Cholesteric liquid crystals

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Feature distillation network based on enhanced full-channel attention for lightweight image super-resolution

Feature distillation network based on enhanced full-channel ...

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2023 International Conference on Image, Signal processing, and Pattern Recognition, ISPP 2023

作者： Li, Quanyin Xiang, Rui Huang, Yan Wang, Guoyou National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510666351

In recent years, deep learning-based methods have made a big splash in the field of single image super-resolution (SISR), and a lot of excellent research works on lightweight image super-resolution networks have emerged. This series of approaches point a way forward for lightweight SR network design, but they generally suffer from two problems: 1) slow convergence of the network 2) poor image reconstruction quality. In this paper, we firstly propose a simple and effective learning rate decay scheme without additional cost, and the new strategy can accelerate the convergence speed of the network, and the model obtained in the same training time is about 0.05 dB higher in PSNR test results. Secondly, we think about the performance bottleneck of RFDN and propose an enhanced full-channel attention (EFA) module with a mixture of channel and spatial attention, which can improve about 0.085 dB in PSNR compared to the CCA attention module. Finally, we propose a new feature distillation network based on the EFA module, called EFAFDN. With only 523k parameters, the EFAFDN(x2) is lighter than the RFDN with 534k parameters and has better SR performance than the RFDN-L with 626k parameters. Extensive experimental results show that EFAFDN performs slightly better than RLFN, the winning model of the main track of the NTIRE 2022 Efficient Super-Resolution Challenge. © 2023 SPIE.

关键词： Distillation

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Pyramid Region-based Slot Attention Network for Temporal Action Proposal Generation 33

Pyramid Region-based Slot Attention Network for Temporal Act...

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33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Li, Shuaicheng Zhang, Feng Zhao, Rui-Wei Yang, Kunlin Liu, Lingbo Feng, Rui Hou, Jun Sensetime Research China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Academy for Engineering and Technology Fudan University Shanghai China The Hong Kong Polytechnic University Hong Kong

It has been found that temporal action proposal generation, which aims to discover the temporal action instances within the range of the start and end frames in the untrimmed videos, can largely benefit from proper temporal and semantic context exploitation. The latest efforts were dedicated to considering the temporal context and similarity-based semantic context through self-attention modules. However, they still suffer from cluttered background information and limited contextual feature learning. In this paper, we propose a novel Pyramid Region-based Slot Attention (PRSlot) modules to address these issues. Instead of using the similarity computation, our PRSlot module directly learns the local relations in an encoder-decoder manner and generates the representation of a local region enhanced based on the attention over input features called slot. Specifically, upon the input snippet-level features, PRSlot module takes the target snippet as query, its surrounding region as key and then generates slot representations for each query-key slot by aggregating the local snippet context with a parallel pyramid strategy. Based on PRSlot modules, we present a novel Pyramid Region-based Slot Attention Network termed PRSA-Net to learn a unified visual representation with rich temporal and semantic context for better proposal generation. Extensive experiments are conducted on two widely adopted THUMOS14 and ActivityNet-1.3 benchmarks. In particular, we improve the AR@100 from the previous best 50.67% to 56.12% for proposal generation and raise the mAP under 0.5 tIoU from 51.9% to 58.7% for action detection on THUMOS14. Code is available at https://***/handhand123/PRSA-Net. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Semantics

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Design of Cross-Shaped CPW-Fed Ultrawideband Slot Antenna

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Journal of Shanghai Jiaotong university(Science) 2018年第6期23卷 834-837页

作者： XIANG Niexin DONG Jiaqiang YAN Dong WANG Ping School of Information Science and Technology Xichang UniversityXichang 615000SichuanChina Key Laboratory of Network Control &Intelligent Instrument Chongqing University of Posts and Telecommunications Chongqing 400065China

A new design of ultrawideband(UWB) antenna of coplanar waveguide(CPW)-fed is proposed. The antenna is composed of a cross-shaped patch and house-shaped slot with the minimum dimension of 21 mm ×20 mm × 1.6 mm. The analysis of S11, VSWR, radiation pattern and surface current is discussed with HFSS simulation software, and also the effect of parameters is presented. Experimental results show that the bandwidth of the antenna covers 110.67%(3.3—11.6 GHz) of UWB range with return loss better than 10 dB. And the good impedance matching in frequency band confirms the antenna is a good candidate for the application of wireless system.

关键词： coplanar waveguide return loss HFSS ultrawideband(UWB)

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Numerical simulations of a bubble growth and departure on the horizontal wall using thermal lattice boltzmann method

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Journal of Computational Multiphase Flows 2015年第2期7卷 111-116页

作者： Wei, Yikun Feng, Kongfang Li, Qifei Faculty of Mechanical Engineering and Automatic Zhejiang Sci-Tech University Province Key Laboratory of Fluid Transmission Technology Hangzhou310018 China Shanghai Key Laboratory of Modern Metallurgy and Materials Processing Shanghai University Shanghai200072 China College of Information Science and Technology Chengdu University of Techonlogy Chengdu610059 China

The process of bubble nucleation, growth and detachment are simulated using thermal lattice Boltzmann method. As the bubble grows to a certain size, it will eventually detach from an active nucleation site especially for the case of a pool boiling of a horizontal wall. Numerical results are compared qualitatively with the experimental results. A qualitative agreement is reached. It can also be concluded that the departure diameter decreases as the wall superheat decreases, while the growing time increases. It is has been ascertained that both growing time and departure diameter increase as gravity decreases.

关键词： Kinetic theory

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Multi-scale reconstruction generative networks for thermal to visible image transformation

Multi-scale reconstruction generative networks for thermal t...

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2023 International Conference on Image, Signal processing, and Pattern Recognition, ISPP 2023

作者： Xiang, Rui Li, Quanyin Huang, Yan Wang, Guoyou National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510666351

In recent years, the field of thermal to visible image transformation has made great progress with Generative Adversarial Network(GAN). Since GANs own the ability to fit the signal frequency, these methods are limited to using more GANs or designing sub-tasks to improve the quality of the generated image. Due to the large difference in the information frequency of individual objects in the image, GANs pay less attention to low-frequency information, which leads to edge distortion of dynamic objects such as people and vehicles in the generated image. Edge distortion has become an important issue for practical applications We propose a new structure and two new loss functions to complete the task of thermal to visible image transformation. Our network takes one thermal image as input and generates a visible RGB image as output. First, we down-sample inputs for three times to get multi-scale inputs. Then we build outputs in multi-scale form small size to large size and fuse the multi-scale outputs. In train stage, our two new losses better direct the network to converge. In order to prove the effectiveness of the proposed thermal to visible image transformation algorithm, we use the KASIT-MPD dataset, which includes real paired thermal and visible images. © 2023 SPIE.

关键词： Generative adversarial networks

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Novel acceleration compensation method for highly squint mode SAR with curve trajectory

Novel acceleration compensation method for highly squint mod...

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IET International Radar Conference 2018, IRC 2018

作者： Zhou, Zhichao Ding, Zegang Zeng, Tao Li, Gen Li, Linghao School of Information and Electronics Beijing Institute Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

Due to the influence of air currents and the control of the platform's own power system, acceleration is often present in the motion platform equipped with synthetic aperture radar (SAR) system, which causes the actual trajectory of the platform to be curved. When the acceleration is large or the azimuth accumulation time is long, a large envelope error or phase error will be caused. This problem will be more obvious in highly squint mode SAR. On the other hand, the acceleration may also cause the situation where the absolute value of the Doppler frequency rate is extremely small, resulting in the azimuthal time-bandwidth product that is too small to satisfy the requirements of the stationary phase principle. To solve the above problems, a novel acceleration compensation method based on inertial navigation information is proposed in this article. By integrating the acceleration and velocity information provided by the inertial navigation system, the position information of maneuvering platform is obtained. Then the actual trajectory of the platform is constructed. On this basis, the envelope and phase errors caused by the acceleration are estimated. The results of real data processing verify the correctness of the analysis and the effectiveness of the proposed method. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Acceleration

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