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International Conference on Dependable Systems and Their Applications (DSA)

作者： Jinchang Hu Kang Sun Sen Yang Zhanwei Hui Song Huang College of Command and Control Engineering Army Engineering University of PLA Nanjing China AVIC The First Aircraft Institute Xi’an China Academy of Military Science China

The autonomous system is an extremely complex and multidisciplinary system, and the overall goal of this paper is to study safety testing methods for autonomous systems to enhance the robustness of autonomous systems. In order to realize an autonomous system with high reliability and robustness, this paper summarizes the security defect detection methods for autonomous systems from the two dimensions of static analysis and dynamic testing and expounds on the syntax-level, semantic, and system-level testing methods for autonomous systems.

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A New Adjacency Matrix Configuration in GCN-based Models for Skeleton-based Action Recognition

arXiv

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arXiv 2022年

作者： Fang, Zheng Zhang, Xiongwei Cao, Tieyong Zheng, Yunfei Sun, Meng Institute of Command and Control Engineering Army Engineering University Jiangsu Nanjing210001 China The Army Artillery and Defense Academy of PLA Jiangsu Nanjing211131 China

Human skeleton data has received increasing attention in action recognition due to its background robustness and high efficiency. In skeleton-based action recognition, graph convolutional network (GCN) has become the mainstream method. This paper analyzes the fundamental factor for GCN-based models - the adjacency matrix. We notice that most GCN-based methods conduct their adjacency matrix based on the human natural skeleton structure. Based on our former work and analysis, we propose that the human natural skeleton structure adjacency matrix is not proper for skeleton-based action recognition. We propose a new adjacency matrix that abandons all rigid neighbor connections but lets the model adaptively learn the relationships of joints. We conduct extensive experiments and analysis with a validation model on two skeleton-based action recognition datasets (NTURGBD60 and FineGYM). Comprehensive experimental results and analysis reveals that 1) the most widely used human natural skeleton structure adjacency matrix is unsuitable in skeleton-based action recognition;2) The proposed adjacency matrix is superior in model performance, noise robustness and transferability. Copyright © 2022, The Authors. All rights reserved.

关键词： Musculoskeletal system

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A Neural Network Approach to Forecasting Computing-Resource Exhaustion with Workload

A Neural Network Approach to Forecasting Computing-Resource ...

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International Conference on Quality Software

作者： Ke-Xian Xue Liang Su Yun-Fei Jia Kai-Yuan Cai Department of Automatic Control Beijing Aeronautics and Astronautics University Beijing China PLA Command and Engineering Institute of Chemical Defence Beijing China

ISBN: (纸本)9781424459124

Software aging refers to the phenomenon that applications will show growing failure rate or performance degradation after longtime execution. It is reported that this phenomenon usually has close relationship with computing-resource exhaustion. This paper analyzes computing-resource usage data collected on a LAN, and quantitatively investigates the relationship between computing-resource exhaustion trend and workload. First, we discuss the definition of workload, and then a multi-layer back propagation neural network is trained to construct the nonlinear relationship between input (workload) and output (computing-resource usage). Then we use the trained neural network to forecast the computing-resource usage, i.e., free memory and used swap, with workload as its input. Finally, the results were benchmarked against those obtained without regard to influence of workload reported in the literatures, such as non-parametric statistical techniques or parametric time series models.

关键词： Neural networks Computer networks Aging Application software Degradation Computer errors Software systems Predictive models Software performance Software quality

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Research on Autonomous Maneuvering Strategies of UAV Swarm for Saturation Attack

Research on Autonomous Maneuvering Strategies of UAV Swarm f...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Zhang, Tingting Zuo, Yi Zhang, Dongning Ding, Fei Huang, Jun Lin, Yun College of Command and Control Engineering Army Engineering University of the Pla Nanjing China Key Laboratory of Information System Requirements Nanjing China Fifty-fourth Research Institute of China Electronics Technology Group Corporation Shijiazhuang China Internet of Things Academy Nanjing University of Posts and Telecommunications Nanjing China Jsti Group Nanjing China Harbin Engineering University Department of Information and Communication Engineering Harbin China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In order to solve the problem of unmanned aerial Vehicle (UAV) cluster saturation attack, the autonomous maneuver strategy of UAV is studied. Based on the distributed partial observable Markov decision process, the autonomous maneuver decision model of UAV is constructed, and the Recurrent Multi-Agent Deep Deterministic Policy Gradient (RMADDPG) is used to learn the maneuver strategy of UAV cluster saturation attack. Combined with the typical characteristics of saturation attack scenario, two reward functions of global reward and local reward for UAV maneuver are designed. The trained UAVs can effectively perform suicide saturation attack task. According to the mission target design evaluation index of saturation attack, the Monte Carlo analysis method is used to compare the proposed method with particle swarm optimization (PSO) algorithm in three aspects: inter aircraft collision avoidance, NFZ avoidance and simultaneous attack. The experimental results show that the trained UAVs can effectively perform the suicide saturation attack task under the condition of a small amount of communication, which provides a method for the application of multi-agent deep reinforcement learning to UAV cluster operations. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Ship wakes detection in SAR images

Ship wakes detection in SAR images

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International Conference on Signal Processing Proceedings (ICSP)

作者： Zhu Weigang Wei Hua Jia Xin Zhou Yinqing Department of Measurement and Control Institute of Command and Technology of Equipment Beijing China School of Electronic Engineering Beijing Aeronautics and Astronautics University Beijing China

Detecting ship wakes from spaceborne SAR images is significant. But it is particularly difficult, especially detecting-thin line features. Because those features are not only affected by speckle but also affected by various other factors and the image resolution is often coarser than the wide of the corresponding objects. In this paper, an algorithm is developed based on line-support regions of similar gradient orientation and the Radon-transform. It was found that this approach works fairly well for the images where the ship wakes are by no means distinct.

关键词： Marine vehicles Image edge detection Speckle Radar detection Surface fitting Transforms Extraterrestrial measurements Space technology Object detection Computer vision

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Decoupling control of Geometrical Consistency for Formation UAVs Based on Node Importance Identification of Temporal Network

Decoupling Control of Geometrical Consistency for Formation ...

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Energy and Electrical engineering (EEE), International Conference on

作者： Yi Zhu Jiguang Li Kai Zhang Hui Tian Kan Zhou College of Field Engineering Army Engineering University of PLA Nanjing China School of Aircraft Xi'an Aeronautical Institute Xi'an China College of Command and Control Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9798350341768

ISBN: (纸本)9798350341775

To address the issue of geometric consistency in the formation of unmanned aerial vehicles (UAVs) during flight, from the perspective of formation control, an identification method for the core nodes of the temporal network is introduced to analyze and evaluate the geometric position error of the UAV formation. A decoupling controller is designed to improve the geometric consistency of the UAV formation. During the design process, the UAVs' dynamics model is established and a Leader-Follower formation controller is designed based on LMI and virtual Leader. The node importance identification of the UAV formation is determined by constructing a time series network according to the similarity based super adjacency matrix (SSAM) of nodes, and the controller is improved in the light of the results of node importance recognition. In the simulation process, the tracking effect of the dual aircraft formation was first verified and analyzed. Then, taking the 6-aircraft formation as an example, the relationship between node importance and geometric consistency was analyzed, and the controller was improved. The simulation results showed that the improved controller, taking into account the factors affecting node importance, can improve the geometric consistency of the formation, providing meaningful reference value for the study of maintaining and consistency control of Formation organization and formation maintenance formations.

关键词： Simulation Time series analysis Process control Organizations Autonomous aerial vehicles Vectors Aircraft Vehicle dynamics Optimization Drones

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GAIL-PT: A Generic Intelligent Penetration Testing Framework with Generative Adversarial Imitation Learning

arXiv

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arXiv 2022年

作者： Chen, Jinyin Hu, Shulong Zheng, Haibin Xing, Changyou Zhang, Guomin Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China College of Information Engineering Zhejiang University of Technology Hangzhou China College of Command and Control Engineering Army Engineering University of PLA Nanjing China

Penetration testing (PT) is an efficient network testing and vulnerability mining tool by simulating a hacker’s attack for valuable information applied in some areas, e.g., the host’s operating and database systems. Compared with manual PT, intelligent PT has become a dominating mainstream due to less time-consuming and lower labor costs. Among the already proposed intelligent PT methods, reinforcement learning (RL) based PT has achieved state-of-the-art (SOTA) performance. Unfortunately, RL-based PT is still challenged in real exploitation scenarios because the agent’s action space is usually high-dimensional discrete, thus leading to algorithm convergence difficulty. Besides, most PT methods still rely on the decisions of security experts. Addressing the challenges, for the first time, we introduce expert knowledge to guide the agent to make better decisions in RL-based PT, and propose a Generative Adversarial Imitation Learning based generic intelligent Penetration Testing framework, denoted as GAIL-PT, to solve the problems of higher labor costs due to the involvement of security experts and high-dimensional discrete action space. Specifically, first, we manually collect the state-action pairs to construct an expert knowledge base when the pre-trained RL / DRL model executes successful penetration testings. Second, we input the expert knowledge and the state-action pairs generated online by the different RL / DRL models into the discriminator of GAIL for training. At last, we apply the output reward of the discriminator to guide the agent to perform the action with a higher penetration success rate to improve PT’s performance. Extensive experiments conducted on the real target host and simulated network scenarios show that GAIL-PT achieves SOTA penetration performance against DeepExploit in exploiting actual target Metasploitable2 and Q-learning in optimizing penetration path, not only in small-scale with or without honey-pot network environments, but also in th

关键词： Reinforcement learning

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The strength of nesterov’s extrapolation in the individual convergence of nonsmooth optimization

TechRxiv

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TechRxiv 2020年

作者： Tao, Qing Tao, Wei Pan, Zhisong Wu, Gaowei Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China Institute of Automation Chinese Academy of Sciences China Army Academy Of Artillery and Air Defense Hefei230031 China

The extrapolation strategy raised by Nesterov, which can accelerate the convergence rate of gradient descent methods by orders of magnitude when dealing with smooth convex objective, has led to tremendous success in training machine learning tasks. In this article, the convergence of individual iterates of projected subgradient (PSG) methods for nonsmooth convex optimization problems is theoretically studied based on Nesterov’s extrapolation, which we name individual convergence. We prove that Nesterov’s extrapolation has the strength to make the individual convergence of PSG optimal for nonsmooth problems. In light of this consideration, a direct modification of the subgradient evaluation suffices to achieve optimal individual convergence for strongly convex problems, which can be regarded as making an interesting step toward the open question about stochastic gradient descent (SGD) posed by Shamir. Furthermore, we give an extension of the derived algorithms to solve regularized learning tasks with nonsmooth losses in stochastic settings. Compared with other state-of-the-art nonsmooth methods, the derived algorithms can serve as an alternative to the basic SGD especially in coping with machine learning problems, where an individual output is needed to guarantee the regularization structure while keeping an optimal rate of convergence. Typically, our method is applicable as an efficient tool for solving large-scale l1-regularized hinge-loss learning problems. Several comparison experiments demonstrate that our individual output not only achieves an optimal convergence rate but also guarantees better sparsity than the averaged solution. © 2020, CC BY.

关键词： Extrapolation

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Impact of Quantum Capacitance on Transmission Characteristics of Carbon Nanotubes Filled Shielded Through-Silicon Vias

Impact of Quantum Capacitance on Transmission Characteristic...

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Jinrong Su Chunhui Yao Xue Chen Wenmei Zhang Dept. Electric and Information Engineering Shanxi University Taiyuan Shanxi China Command and control division North Automatic Control Technology Institute Taiyuan China College of Physics and Electronics Shanxi University Taiyuan Shanxi China

ISBN: (纸本)9781538612422

Shielded through-silicon vias (S-TSV) filled with multi-walled carbon nanotubes (MWCNT) in the via and the shielded layer, and benzocyclobutene or silicon in the insulation layer is presented in this paper. Then, the equivalent transmission line models of the two S-TSVs are established. Based on the model, the forward transmission coefficient and attenuation constant are calculated and the impact of quantum capacitance C q of MWCNT on the transmission performance of S-TSVs is analyzed. The results indicate that the performance of S-TSVs with Si insulation layer in 0-100 GHz can be significantly improved by C q . Also, the performance of S-TSV filled with BCB above 40 GHz can be improved. In addition, the temperature effect of silicon can be balanced by C q . As a result, the heat stability of S-TSV with silicon insulation layer is improved.

关键词： Quantum capacitance Through-silicon vias Integrated circuit modeling Silicon Insulation Electron devices

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On separating the information of slow-mode angular motion of projectile

On separating the information of slow-mode angular motion of...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Yuanqin Wang Ruoyu Zhang Jing Sun Institute of Ultra-precision Optical & Electronic Instrument Engineering Harbin Institute of Technology Harbin China Academy of Equipment Command슠and슠Technology Beijing China Beijing Aerospace Control Center Beijing China

The information on angular motion of projectile can be expressed by the Amplitude Modulation (AM) index of radar echo. In order to separate the information of slow-mode angular motion, a method based on Empirical Mode Decomposition (EMD) is proposed. Three issues are discussed in this article. First, the angular motion of projectile is approximated as a fast-mode circle superposing over that of the slow-mode according to the theory of exterior ballistics. Next, the characteristics of AM index that can represent the angular motion are discussed. Considering the effects of Discrete Fourier Transform (DFT) and the interference of noise, the index of AM is modeled as nonstationary time series in which the slow fluctuation corresponds to the slow-mode circular motion. Then an EMD-based separating method is suggested to obtain the index of the slow-mode motion. It includes two steps. The first step is to divide the index into a series of Intrinsic Mode Functions (IMFs) and the residual item. The second step is to reconstruct the index of the slow-mode motion with the components of the lower frequency IMFs and the residual by utilizing the prior knowledge about the difference in the periods. Compared with theoretical value and the result of stationary wavelet transform, as well as the in-flight experiment, the results show the validity and effectiveness.

关键词： Indexes Projectiles Discrete Fourier transforms Time series analysis Noise Wavelet transforms

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