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HTTP-sCAN:Detecting HTTP-Flooding Attack by Modeling Multi-Features of Web Browsing Behavior from Noisy Web-Logs

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china communications 2015年第2期12卷 118-128页

作者： WANG Jin ZHANG Min YANG Xiaolong long keping xu jie school of Computer and communications engineering University of Science and Technology Beijing Network Center of chengdu university Research Center for Optical Internet & Mobile information Network School of Communication & Information EngineerUniversity of Electronic Science & Technology of China

HTTP-flooding attack disables the victimized web server by sending a large number of HTTP Get *** research tends to detect HTTP-flooding with the anomaly-based approaches,which detect the HTTP-flooding by modeling the behavior of normal web ***,most of the existing anomaly-based detection approaches usually cannot filter the web-crawling traces from unknown searching bots mixed in normal web browsing *** web-crawling traces can bias the base-line profile of anomaly-based schemes in their training phase,and further degrade their detection *** paper proposes a novel web-crawling tracestolerated method to build baseline profile,and designs a new anomaly-based HTTP-flooding detection scheme(***-sCAN).The simulation results show that HTTP-sCAN is immune to the interferences of unknown webcrawling traces,and can detect all HTTPflooding attacks.

关键词： IP network DDoS relative entropy cluster algorithm

The In-Flight Realtime Trigger and Localization Software of GECAM

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Research in Astronomy and Astrophysics 2024年第10期24卷 11-24页

作者： Xiao-Yun Zhao Shao-Lin Xiong Xiang-Yang Wen Xin-Qiao Li Ce Cai Shuo Xiao Qi Luo Wen-Xi Peng Dong-Ya Guo Zheng-Hua An Ke Gong Jin-Yuan Liao Yan-Qiu Zhang Yue Huang Lu Li Xing Wen Fei Zhang Jing Duan Chen-Wei Wang Dong-Li Shi Peng Zhang Qi-Bin Yi Chao-Yang Li Yan-Bing xu Xiao-Hua Liang Ya-Qing liu Da-Li Zhang Xi-Lei Sun Fan Zhang Gang Chen Huan-Yu Wang Sheng Yang Xiao-Jing liu Min Gao Mao-Shun Li Jin-Zhou Wang Xing Zhou Yi Zhao Wang-Chen xue Chao Zheng Jia-Cong liu Xing-Bo Han Jin-Ling Qi Jia Huang Ke-Ke Zhang Can Chen Xiong-Tao Yang Dong-jie Hou Yu-Sa Wang Rui Qiao Xiang Ma Xiao-Bo Li Ping Wang Xin-Ying Song Li-Ming Song Shi-jie Zheng Bing Li Hong-Mei Zhang Yue Zhu Wei Chen jian-jian He Zhen Zhang Jin Hou Hong-Jun Wang Yan-Chao Hao Xiang-Yu Wang Zong-Yuan Yang Zhi-long Wen Zhi Chang Yuan-Yuan Du Rui Gao Xiao-Fei Lan Yan-Guo Li Gang Li xu-Fang Li Fang-Jun Lu Hong Lu Bin Meng Feng Shi Hui Wang Hui-Zhen Wang Yu-Peng xu Jia-Wei Yang xue-Juan Yang Shuang-Nan Zhang Chao-Yue Zhang Cheng-Mo Zhang Zhi-Cheng Tang Cheng Cheng Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China university of Chinese Academy of sciences Chinese Academy of SciencesBeijing 100049China school of information science and technology Southwest Jiaotong UniversityChengdu 611756China Key Laboratory of Stellar and Interstellar Physics and Department of Physics Xiangtan UniversityXiangtan 411105China Physics and Space science College China West Normal UniversityNanchong 637002China Department of Astronomy Beijing Normal UniversityBeijing 100875China Innovation Academy for Microsatellites of CAS Shanghai 201203China Changchun university of science and technology Changchun 130022China Chinese Academy of sciences South America Center for Astronomy National Astronomical ObservatoriesCASBeijing 100101China

Realtime trigger and localization of bursts are the key functions of GECAM,an all-sky gamma-ray monitor launched on 2020 December *** developed a multifunctional trigger and localization software operating in the CPU of the GECAM electronic *** onboard software has the following features:high trigger efficiency for real celestial bursts with a suppression of false triggers caused by charged particle bursts and background fluctuation,dedicated localization algorithm optimized for both short and long bursts,and low time latency of the trigger information which is downlinked through the Global Short Message communication service of the global BeiDou navigation *** paper provides a detailed description of the design and development of the trigger and localization software system for *** covers the general design,workflow,the main functions,and the algorithms used in the *** paper also includes on-ground trigger tests using simulated gamma-ray bursts generated by a dedicated X-ray tube,as well as an overview of the performance for real celestial bursts during its in-orbit operation.

关键词： telescopes instrumentation:detectors methods:observational

Robust DOA estimation and tracking for integrated sensing and communication massive MIMO OFDM systems

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science china(information sciences) 2023年第10期66卷 278-296页

作者： Kui xu Xiaochen XIA Chunguo LI Wei XIE jie liu Rangang ZHU Huasen HE College of communications engineering Army Engineering University of PLA school of information science and engineering Southeast University school of electronic Countermeasures National University of Defense Technology school of information science and technology University of Science and Technology of China

In this paper, we propose a robust direction-of-arrival(DOA) estimation and tracking scheme for a massive multiple input multiple output(MIMO) orthogonal frequency-division multiplexing(OFDM)system using integrated sensing and communication(ISAC). First, a frame structure is designed to enable integrated DOA estimation and tracking, as well as data transmission. Then, coherent combining and multipath combining methods are proposed as pilot signal preprocessing methods for robust DOA estimation and tracking. Finally, for ISAC massive MIMO-OFDM systems, a fast Fourier transform(FFT) algorithmbased robust DOA estimator design is proposed, including a preamble-based initial DOA estimation scheme and an embedded pilot-based DOA tracking scheme. The simulation results demonstrate that the proposed robust DOA estimation and tracking method can obtain accurate DOA estimation even when the signal-tonoise ratio is low. Furthermore, the estimation performance outperforms the conventional multiple signal classification(MUSIC) and estimation of signal parameters via rotational invariance technique(ESPRIT)methods.

关键词： integrated sensing and communication massive multiple input multiple output (MIMO) orthogonal frequency-division multiplexing (OFDM) direction-of-arrival (DOA) estimation and tracking frame structure and pilot sequence

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基于时延光子储备池计算的混沌激光短期预测

物理学报 2021年第15期70卷 156-162页

作者：刘奇李璞开超胡春强蔡强张建国徐兵杰太原理工大学新型传感器与智能控制教育部重点实验室太原030024 广东工业大学信息工程学院广州510006 广东省光子学信息技术重点实验室广州510006 中国电子科技集团公司第三十研究所成都610041 西南通信研究所保密通信重点实验室成都610041

提出并证明了一种利用时延光子储备池计算短期预测混沌激光的时间序列.具体来说,建立基于光反馈和光注入半导体激光器的储备池结构,通过选择合适的系统参数,时延光子储备池计算可以有效地预测混沌激光约2 ns的动态轨迹.此外,研究了系统... 详细信息

提出并证明了一种利用时延光子储备池计算短期预测混沌激光的时间序列.具体来说,建立基于光反馈和光注入半导体激光器的储备池结构,通过选择合适的系统参数,时延光子储备池计算可以有效地预测混沌激光约2 ns的动态轨迹.此外,研究了系统参数对预测结果的影响,包括掩模类型、虚拟节点数、训练数据长度、输入增益、反馈强度、注入强度、岭参数和泄漏率.作为一种具有全光实现潜力的机器学习方法,时延光子储备池具有结构简单、训练成本低、易于硬件实现等优点.

关键词：储备池计算预测混沌激光机器学习

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基于神经网络的配网电气拓扑识别算法

电子科技大学学报 2023年第2期52卷 247-253页

作者：刘丽娜王韬周一飞程志炯李方硕张昱航徐杰国网四川省电力公司计量中心成都610045 电子科技大学信息与通信工程学院成都611731

提出了一种基于多通道自适应加权神经网络的配网电气拓扑识别算法,构建了多通道一维卷积神经网络(1DCNN)模型,以电压、电流、功率和功率因数4种采集数据作为各通道的输入数据,通过两层叠加的卷积模块实现特征提取;同时,提出了一种自适... 详细信息

提出了一种基于多通道自适应加权神经网络的配网电气拓扑识别算法,构建了多通道一维卷积神经网络(1DCNN)模型,以电压、电流、功率和功率因数4种采集数据作为各通道的输入数据,通过两层叠加的卷积模块实现特征提取;同时,提出了一种自适应加权的特征融合方案,通过神经网络自适应学习各通道重要性特征。实验采用真实用电数据制作数据集,并针对通道数、数据种类、数据维度等参数进行了多组实验。实验结果表明,该算法融合多种用电数据特征,配网电气拓扑辨识准确率达到99.772%。

关键词：自适应加权深度学习配网电气拓扑识别特征融合多通道模型

基于振动信号显著性序列的滚动轴承状态诊断方法研究

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机电工程 2021年第8期38卷 944-951页

作者：刘志翔朱明付铭梅杰徐惠聂德鑫李永祥国网山西省电力公司电力科学研究院山西太原030001 华中科技大学电子信息与通信学院湖北武汉430074 南瑞集团(国网电力科学研究院)有限公司江苏南京211106 国网电力科学研究院武汉南瑞有限责任公司湖北武汉430074

为提升基于时域信号的滚动轴承状态诊断准确率,提出了一种基于振动信号显著性序列的滚动轴承状态诊断方法。首先,将采集得到的振动信号归一化后进行了傅里叶变换,得到对数幅度谱和平均对数谱,并将二者相减获得了信号的谱残差;然后,对谱... 详细信息

为提升基于时域信号的滚动轴承状态诊断准确率,提出了一种基于振动信号显著性序列的滚动轴承状态诊断方法。首先,将采集得到的振动信号归一化后进行了傅里叶变换,得到对数幅度谱和平均对数谱,并将二者相减获得了信号的谱残差;然后,对谱残差通过傅里叶逆变换映射回时间域,得到了信号的显著性序列;最后,将显著性序列输入到状态诊断模型中,对滚动轴承运行状态进行了分类,实现了对滚动轴承的状态诊断。实验及研究结果表明:相对于原振动信号,显著性序列可以有效地提高分类准确率,特别是对信噪比(SNR)较差的振动信号,如混有-6 dB的高斯白噪声,以支持向量机(SVM)及卷积神经网络(CNN)分别作为状态诊断模型,显著性序列的状态诊断准确率较原振动信号可分别提高9%和10.75%;对于利用卷积神经网络的状态诊断模型,显著性序列还能有效缩短网络模型训练时间,提高系统的时效性。

关键词：振动信号滚动轴承状态诊断显著性序列谱残差机器学习