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International Conference on Communication technology (ICCT)

作者： Lan Zhang Liang Ma Feng Tian Tianyi Liang Science and Technology on Communication Information Security Control Laboratory Jiaxing China The 36th Research Institution of China Electronics Technology Group Corporation Jiaxing China Nanjing University of Posts and Telecommunications Nanjing China

In order to effectively cope with the external malicious jamming from jammers and avoid mutual interference caused by competitive channels among users, an intelligent antijamming decision-making method based on deep reinforcement learning for multi-user communication is proposed in this paper. In multiple jamming modes, the base station perceives the current spectrum information of the multi-user and the jammer and makes it as the input of the deep reinforcement learning strategy neural network, then selects the joint action according to the dynamic greedy algorithm, which will help the users intelligently select the communication frequency band via the feedback from the base station. The simulation results show that the proposed method effectively overcome the communication jamming induced by external jammers and internal users. Moreover, the normalized throughput of each user in the proposed algorithm is much higher than the random frequency hopping and fixed ε deep reinforcement learning algorithm with faster convergence speed.

关键词： Deep learning Base stations Simulation Heuristic algorithms Decision making Reinforcement learning Spread spectrum communication

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Passive Target Detection Based on GLRT Using Multi-satellite Illumination 3rd

Passive Target Detection Based on GLRT Using Multi-satellite...

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3rd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2021

作者： Zhu, Huijie Liu, Mingqian Li, Ming Gao, Xiuhui Science and Technology on Communication Information Security Control Laboratory The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China State Key Laboratory of Integrated Service Networks Xidian University Shaanxi Xi’an710071 China State 722 Factory Guangxi Guilin541001 China

ISBN: (纸本)9783030901950

This paper proposes a novel passive location parameter estimator using multiple satellites for moving aerial targets. Specifically, we consider target detection in the ground dual receiver system, which is divided into reference channel and monitoring channel. The reference channel receives the direct wave signals from multiple external emitters, and the monitoring channel receives the echo signals reflected by the target. We propose a target detection method based on a generalized likelihood ratio (GLRT). This detection algorithm is robust to the reference channel noise. Extensive simulations are conducted to evaluate the performance of the algorithm under various network settings. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Satellites

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Passive Target Detection Based on Rao Using Multi-satellite Illumination 3rd

Passive Target Detection Based on Rao Using Multi-satellite ...

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3rd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2021

ISBN: (纸本)9783030901950

In this paper, hypotheses of target detection features is proposed when constructing the signal model. Under this condition, the Rao detection method is extended to weak echo signal detection using multi-satellite illumination. Furthermore, a multi-satellite weak echo signal detection algorithm is proposed based on Rao detection. When the noise variance is unknown, the Rao detector is designed according to the existence of an interfering target. Moreover, the detector’ detection thresholds are obtained given the false alarm probability, respectively. Finally, we evaluate the Rao detection performance in different situations with extensive simulations. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Satellites

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Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless Networks

TechRxiv

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TechRxiv 2022年

作者： Zhang, Yuanyu Zheng, Zhumeng He, Ji Zhao, Shuangrui Qu, Qianyue Shen, Yulong Jiang, Xiaohong School of Computer Science and Technology Xidian University Shaanxi Xi’an China Shannxi Key Laboratory of Network and System Security China The Beijing Sunwise Information Technology Ltd Beijing Institute of Control Engineering Beijing China The Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan School of Systems Information Science Future University Hakodate Hokkaido Hakodate Japan

While the millimeter-wave (mmWave) communication is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack. © 2022, CC BY.

关键词： Millimeter waves

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LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection

arXiv

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arXiv 2024年

作者： Tian, Jiwei Shen, Chao Wang, Buhong Xia, Xiaofang Zhang, Meng Lin, Chenhao Li, Qian Ministry of Education Key Laboratory for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Xi’an China Air Traffic Control and Navigation College Air Force Engineering University Xi’an China Information and Navigation College Air Force Engineering University Xi’an China School of Computer Science and Technology Xidian University Xi’an China

—Deep learning methods can not only detect false data injection attacks (FDIA) but also locate attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on deep learning vulnerabilities have been studied in the field of single-label FDIA detection, the adversarial attack and defense against multi-label FDIA locational detection are still not involved. To bridge this gap, this paper first explores the multi-label adversarial example attacks against multi-label FDIA locational detectors and proposes a general multi-label adversarial attack framework, namely muLti-labEl adverSarial falSe data injectiON attack (LESSON). The proposed LESSON attack framework includes three key designs, namely Perturbing State Variables, Tailored Loss Function Design, and Change of Variables, which can help find suitable multi-label adversarial perturbations within the physical constraints to circumvent both Bad Data Detection (BDD) and Neural Attack Location (NAL). Four typical LESSON attacks based on the proposed framework and two dimensions of attack objectives are examined, and the experimental results demonstrate the effectiveness of the proposed attack framework, posing serious and pressing security concerns in smart grids. © 2024, CC BY.

关键词： Location

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Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless Networks

arXiv

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arXiv 2022年

作者： Zhang, Yuanyu Zheng, Zhumeng He, Ji Zhao, Shuangrui Qu, Qianyue Shen, Yulong Jiang, Xiaohong School of Computer Science and Technology Xidian University Shaanxi Xi’an China Shannxi Key Laboratory of Network and System Security China Beijing Sunwise Information Technology Ltd Beijing Institute of Control Engineering Beijing China Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan School of Systems Information Science Future University Hakodate Hokkaido Hakodate Japan

关键词： Millimeter waves

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yihan Zhao Xuting Duan Jianshan Zhou Long Zhang State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory School of Transportation Science and Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time.

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Contrast enhancement of optical videoscope images

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Iran Journal of Computer science 2023年第3期6卷 261-275页

作者： Ammar, Reda Aboshosha, Sahar El-Hag, Noha A. Saifeldeen, Reda El-Shafai, Walid El-Banby, Ghada M. Ashiba, Huda I. Khalaf, Ashraf A. M. Elazm, Atef Abou El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. El-Safrawey, Amir Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Comm. Faculty of Engineering Minia University Minya Egypt Department of Management of Information Systems Higher Institute of Commercial Science El-Mahala El-Kobra Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Communications Engineering Bilbis Higher Institute of Engineering Sharqia Bilbis Egypt Security Engineering Laboratory Computer Science Department Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. The second framework depends on homomorphic processing. The third framework is based on the homomorphic enhancement with histogram equalization. The first one is superior from the entropy perspective, while the third one is superior from the contrast perspective. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Fuzzy enhancement Histogram equalization Homomorphic enhancement Spectral entropy

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Analysis of Attack Effectiveness Evaluation of AD hoc Networks based on Rough Set Theory

Analysis of Attack Effectiveness Evaluation of AD hoc Networ...

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International Conference on Computational Intelligence and security

作者： Jiahao Dai Yongqun Chen Science and Technology on Communication Information Security Control Laboratory China Electronic Corporation NO.36 Institute Jiaxing China

ISBN: (纸本)9781665494908

This paper mainly studies an attack effectiveness evaluation method for AD hoc networks based on rough set theory. Firstly, we use OPNET to build AD hoc network simulation scenario, design and develop attack module, and obtain network performance parameters before and after the attack. Then the rough set theory is used to evaluate the attack effectiveness. The results show that this method can effectively evaluate the performance of AD hoc networks before and after attacks.

关键词： Rough sets Data processing Ad hoc networks security Indexes Computational intelligence

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Adaptive ELM-Based Time-Constrained control of Uncertain Robotic Manipulators With Minimum Learning Computation

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IEEE Transactions on Emerging Topics in Computing 2025年

作者： Jin, Xiaozheng Hou, Yuhan Wu, Xiaoming Chi, Jing Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Shandong Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Jinan250013 China Qilu Institute of Technology School of Intelligent Manufacturing and Control Engineering Shandong Jinan250200 China Shandong University of Finance and Economics School of Computing and Artificial Intelligence Shandong Jinan250014 China

This paper studies the extreme learning machine (ELM)-based time-constrained trajectory tracking control of a class of robotic manipulator systems with model/input uncertainties, matched and mismatched disturbances. A uniform robust exact differentiator (URED) is developed to construct a multi-layer virtual control framework of the robotic manipulator system. Under the control framework, adaptive ELM-based control strategies are proposed to suppress the influence of the uncertainties and disturbances layer-by-layer, combining with the minimum learning parameter (MLP) technique which is employed to reduce the calculation complexity of ELM parameters. The significance of this study is that general model/input uncertainties, matched and mismatched disturbances can be effectively compensated within a limited time, so that bounded trajectory tracking of the robotic manipulator can be achieved avoiding the complexity explosion issue. The time-constrained stability of the closed-loop robotic error systems is proved through Lyapunov stability theory. Finally, comparative simulations are employed to display the feasibility and superiority of the designed robust adaptive ELM-based control schemes of a robotic manipulator system. © 2013 IEEE.

关键词： Robust control

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