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FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

Chinese Journal of Electronics 2024年第1期33卷 58-71页

作者： Zeyi LI pan WANG Zixuan WANG School of Computer Science Nanjing University of Posts and Telecommunications School of Modern Posts Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Deep learning Machine learning algorithms Computational modeling Network intrusion detection Imaging Telecommunication traffic Generative adversarial networks

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Polynomial-Time Key-Recovery Attacks Against NTRURe Encrypt from ASIACCS'15

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Journal of Systems Science & Complexity 2024年第3期37卷 1308-1325页

作者： LIU Zhen pan Yanbin ZHENG Jinwei School of Cyber Science and Technology Hubei Key Laboratory of Applied MathematicsHubei UniversityWuhan 430062China Key Laboratory of Mathematics Mechanization Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100190China

In ASIACCS 2015, Nu nez, et al. proposed a proxy re-encryption scheme, named NTRURe Encrypt, based on NTRU, which allows a proxy to translate ciphertext under the delegator’s public key into a re-encrypted ciphertext that can be decrypted correctly by delegatee’s private key. Because of the potential resistance to quantum algorithm, high efficiency and various applications in real life,NTRURe Encrypt has drawn lots of attention and its security has been widely discussed and *** PQCrypto2019, Liu, et al. proposed two key recovery attacks against it. However, their first attack heavily relies on a weaken decryption oracle, and the second attack needs to collect about 260ciphertexts from the same message by theoretical analysis, which makes both of the attacks unrealistic. In this paper, inspired by the broadcast attack against NTRU, the authors find out that for NTRURe Encrypt the delegator and the delegatee can efficiently recover each other’s private key in polynomial time without any unrealistic assumptions. In addition, the authors also show how to fix NTRURe Encrypt to resist the proposed attacks. As a by-product, the authors also show how to commit broadcast attacks against NTRU 2001 with even dg, which was thought infeasible before.

关键词： Broadcast attack key recovery NTRU NTRUReEncrypt

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Research Progress on Bio‑inspired Flapping‑Wing Rotor Micro Aerial Vehicle Development

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Journal of Bionic Engineering 2024年第4期21卷 1621-1643页

作者： Yingjun pan shijun Guo Xun Huang Centre for Aeronautics School of AerospaceTransport and ManufacturingCranfield UniversityBedford MK430ALUK

Flapping-wing rotor(FWR)is an innovative bio-inspired micro aerial vehicle capable of vertical take-off and *** unique design combines active flapping motion and passive wing rotation around a vertical central shaft to enhance aerodynamic *** research on FWR,though relatively new,has contributed to 6%of core journal publications in the micro aerial vehicle field over the past two *** paper presents the first comprehensive review of FWR,analysing the current state of the art,key advances,challenges,and future research *** review highlights FWR’s distinctive kinematics and aerodynamic superiority compared to traditional flapping wings,fixed wings,and rotary wings,discussing recent breakthroughs in efficient,passive wing pitching and asymmetric stroke amplitude for lift *** experiments and remote-controlled take-off and hovering tests of single and dual-motor FWR models have showcased their *** review compares FWR flight performance with well-developed insect-like flapping-wing micro aerial vehicles as the technology readiness level progresses from laboratory to outdoor flight testing,advancing from the initial flight of a 2.6 g prototype to the current free flight of a 60-gram *** review also presents ongoing research in bionic flexible wing structures,flight stability and control,and transitioning between hovering and cruise flight modes for an FWR,setting the stage for potential applications.

关键词： Flapping-wing rotor Micro aerial vehicle Bio-inspiration Flight

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Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 673-689页

作者： Cong pan Junran Peng Zhaoxiang Zhang the Center for Research on Intelligent Perception and Computing(CRIPAC) National Laboratory of Pattern Recognition(NLPR)Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 the School of Future Technology University of Chinese Academy of Sciences(UCAS)Beijing 100049China the Huawei Inc. Beijing 100085China IEEE the Institute of Automation Chinese Academy of Sciences(CASIA)Beijing 100190 the University of Chinese Academy of Sciences(UCAS) Beijing 100049 the Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science&Innovation Chinese Academy of Sciences(HKISI CAS)Hong Kong 999077China

Monocular 3D object detection is challenging due to the lack of accurate depth *** methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB ***-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion ***,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with *** from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth *** we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each ***,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input *** method is the first Swin-Transformer-based backbone architecture for monocular 3D object *** experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.

关键词： Monocular 3D object detection normalizing flows Swin Transformer

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An Encoding-Decoding Framework Based on CNN for circ RNA-RBP Binding Sites Prediction

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Chinese Journal of Electronics 2024年第1期33卷 256-263页

作者： Yajing GUO Xiujuan LEI Yi pan School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Department of Computer Science Georgia State University

Predicting RNA binding protein(RBP) binding sites on circular RNAs(circ RNAs) is a fundamental step to understand their interaction mechanism. Numerous computational methods are developed to solve this problem, but they cannot fully learn the features. Therefore, we propose circ-CNNED, a convolutional neural network(CNN)-based encoding and decoding framework. We first adopt two encoding methods to obtain two original matrices. We preprocess them using CNN before fusion. To capture the feature dependencies, we utilize temporal convolutional network(TCN) and CNN to construct encoding and decoding blocks, respectively. Then we introduce global expectation pooling to learn latent information and enhance the robustness of circ-CNNED. We perform circ-CNNED across 37 datasets to evaluate its effect. The comparison and ablation experiments demonstrate that our method is superior. In addition, motif enrichment analysis on four datasets helps us to explore the reason for performance improvement of circ-CNNED.

关键词： Proteins RNA Neural networks Encoding Robustness Decoding Convolutional neural networks

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A numerical simulation strategy for a compressor’s underlying axisymmetric characteristic and its application in body force model

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Chinese Journal of Aeronautics 2024年第8期37卷 79-90页

作者： shijie LIU Tianyu pan Qiushi LI ` School of Energy and Power Engineering Beihang UniversityBeijing 100191China Research Institute of Aero-Engine Beihang UniversityBeijing 100191China Key Laboratory of Fluid and Power Machinery Ministry of EducationXihua UniversityChengdu 610039China

Accurate prediction of the aerodynamic response of a compressor under inlet distortion is crucial for next-generation civil aircraft,such as Boundary Layer Ingestion(BLI)silent ***,research on the Body Force(BF)model plays a significant role in achieving this ***,distorted inlet airflow can lead to varying operating conditions across different spatial locations of the compressor,which may cause some regions to operate outside the stability ***,the accuracy of BF model simulations might be *** address this issue,this paper proposes a numerical simulation strategy for acquiring the steady axisymmetric three-dimensional flow field of a compressor operating at low mass flow rates,which is known as the Underlying Axisymmetric Pressure Rise Characteristic(UAPRC).The proposed simulation accounts for two different rotor speeds of a transonic compressor and identifies initial positions in the flow field where deterioration occurs based on prior experimental ***,simulation results are incorporated into the BF model to replicate hub instability observed in *** results demonstrate that this strategy provides valid predictions of the UAPRC of the compressor,thereby addressing the limitations associated with the BF model.

关键词： Compressor partial instability Performance at low mass flow rates Underlying axisymmetric pressure rise characteristic Novel simulation strategy Body force model

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Multi-agent reinforcement learning behavioral control for nonlinear second-order systems

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Frontiers of Information Technology & Electronic Engineering 2024年第6期25卷 869-886页

作者： Zhenyi ZHANG Jie HUANG Congjie pan College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108China G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Reinforcement learning behavioral control(RLBC)is limited to an individual agent without any swarm mission,because it models the behavior priority learning as a Markov decision *** this paper,a novel multi-agent reinforcement learning behavioral control(MARLBC)method is proposed to overcome such limitations by implementing joint ***,a multi-agent reinforcement learning mission supervisor(MARLMS)is designed for a group of nonlinear second-order systems to assign the behavior priorities at the decision *** modeling behavior priority switching as a cooperative Markov game,the MARLMS learns an optimal joint behavior priority to reduce dependence on human intelligence and high-performance computing *** the control layer,a group of second-order reinforcement learning controllers are designed to learn the optimal control policies to track position and velocity signals *** particular,input saturation constraints are strictly implemented via designing a group of adaptive *** simulation results show that the proposed MARLBC has a lower switching frequency and control cost than finite-time and fixed-time behavioral control and RLBC methods.

关键词： Reinforcement learning Behavioral control Second-order systems Mission supervisor

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shape optimisation of basin insulator for DC gas insulated switchgear/gas insulated transmission lines based on artificial bee colony algorithm

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High Voltage 2024年第2期9卷 275-286页

作者： Yi Luo shiyi Mao Ju Tang Zijun pan Cheng pan State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhanChina

The surface charge accumulation on the basin insulator is a particular problem in high-voltage direct current(HVDC)gas insulated switchgears(GIS)and gas insulated trans-mission lines(GIL),which restricts the development and application of extra/ultra high-voltage(EHV/UHV)*** surface charge distribution and anti-flashover performance are closely related to the insulator *** obtain the optimal basin insulator,a shape optimisation model based on artificial bee colony algorithm was established,and the minimisation objective functions based on capacitive(initial)electric field distribution and resistive(steady-state)electric field distribution were respectively *** optimisation results of the two objective functions were calculated,and the electric field and charge distribution on the surface of the insulator before and after optimisation were evaluated and compared using the simulation *** results indicated that the optimisation based on the capacitive electric field can significantly inhibit the surface charge accumulation,and the optimised insulator can significantly reduce the surface normal electric field and make the distribution of the tangential electric field more uniform,and the maximum tangential electric field can be reduced by 10%;the optimisation based on resistive electric field can achieve similar results,but requires more computational *** on the results,the‘anti-charge’basin insulator structure suitable for the DC field was given.

关键词： insulator artificial charge

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2-local unstable homotopy groups of indecomposable A32-complexes

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Science China Mathematics 2024年第3期67卷 607-626页

作者： Zhongjian Zhu Jianzhong pan College of Mathematics and Physics Wenzhou University Hua Loo-Keng Key Laboratory of Mathematics Institute of MathematicsAcademy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

In this paper,we calculate the 2-local unstable homotopy groups of indecomposable *** main technique used is analysing the homotopy property of J(A,X),defined by Gray(1973) for a CW-pair(X,A),which is homotopy equival... 详细信息

关键词： homotopy groups A 2 n -complexes fibration sequence relative James construction 55P15

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Event-triggered predefined-time control for full-state constrained nonlinear systems: A novel command filtering error compensation method

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Science China(Technological Sciences) 2024年第9期67卷 2867-2880页

作者： pan YingNan CHEN YiLin LIANG HongJing College of Control Science and Engineering Bohai UniversityJinzhou 121013China School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China

In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sliding mode differentiator, the inherent computational complexity problem within the predefined-time backstepping framework is solved. Different from the existing command filter-based finite-time and fixed-time control strategies that the convergence time of the filtering error is adjusted through the system initial value or numerous parameters, a novel command filtering error compensation method is presented,which tunes one control parameter to make the filtering error converge in the predefined time, thereby reducing the complexity of design and analysis of processing the filtering error. Then, an improved event-triggered mechanism(ETM) that builds upon the switching threshold strategy, in which an inverse cotangent function is designed to replace the residual term of the ETM,is proposed to gradually release the controller's dependence on the residual term with increasing time. Furthermore, a tan-type nonlinear mapping technique is applied to tackle the time-varying full-state constraints problem. By the predefined-time stability theory, all signals in the uncertain nonlinear systems exhibit predefined-time stability. Finally, the feasibility of the proposed algorithm is substantiated through two simulation results.

关键词： predefined-time control command filtering error compensation method event-triggered mechanism time-varying full-state constraints uncertain nonlinear systems

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