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Optically transparent graphene-based cognitive metasurface for adaptive frequency manipulation

Photonics Research 2023年第1期11卷 129-136页

作者： MINGYANG GENG XIAOLU YANG HAO CHEN XINZHI BO MENGZI LI ZHENGUO LIU WEIBING LU State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China Center for Flexible RF Technology Frontiers Science Center for Mobile Information Communication and SecuritySoutheast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China

Optically transparent microwave absorbing metasurfaces have shown great potential and are needed in multiple applications environments containing optical windows owing to their ability to reduce backscattering electromagnetic(EM)signals while keeping continuous optical ***,they are also required to have adaptive EM manipulation capability to cope with complex and capricious EM *** a general approach,distributed circuit components,including positive-intrinsic-negative diodes and varactors and sensing components,are integrated with passive absorbing metasurfaces to realize adaptive control of microwave ***,these circuit elements generally require bulky electrical wires and complex control circuits to regulate the operating state,resulting in the absorbing structures being optically ***,it is a great challenge to realize self-operating absorbers while maintaining optical ***,we report an optically transparent cognitive metasurface made of patterned graphene sandwich structures and a radio frequency detector,which can achieve adaptive frequency manipulation to match incident EM *** a proof-of-principle application example,we realize a closed-loop automatic absorber system prototype of the proposed graphene metasurface with self-adaptive frequency variation,without any human *** approach may facilitate other adaptive metadevices in microwave regime with high-level recognition and manipulation and,more generally,promote the development of intelligent stealth technologies.

关键词： transparent microwave absorber

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Influence of Physical Parameters on Echo Spectrum of Underwater Target

Influence of Physical Parameters on Echo Spectrum of Underwa...

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IEEE/OES China Ocean Acoustics (COA)

作者： Yunfei Chen Dapeng Yu Bing Jia Zhenshan Wang Jintao Yong Yanjie Wang School of Information and Communication Engineering Dalian University of Technology Dalian China Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

The elastic scattering features of the underwater target scattering wave depend on the physical parameters of the target, such as the material and structure. Intuitively evaluating the influence of the elastic scattering wave on the characteristics of the whole scattering wave signal is difficult due to the coupling and superposition of the elastic scattering wave and the geometric scattering wave of the target. Based on the different modulation characteristics of broadband echo spectrum produced by target geometry scattering and elastic scattering wave, this paper characterizes and studies the modulation features of echo spectrum and tests the influence of physical parameters on the echo spectrum of underwater target using several simple cylindrical targets with different physical parameters. Moreover, the geometric scattering wave and the elastic scattering wave of the simple target echo are extracted using the fractional Fourier transform (FrF $T$ ) domain filtering method, and the influence of physical parameters on the echo spectrum is quantitatively analyzed.

关键词： Geometry Couplings Fourier transforms Filtering Oceans Scattering Modulation Feature extraction Acoustics Broadband communication

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Polar Coded OFDM with Code-Frequency Index Modulation

Polar Coded OFDM with Code-Frequency Index Modulation

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International Conference on communication technology (ICCT)

作者： Jia-Qi Zhang Si-Yu Zhang School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

In this paper, we introduce a polar coded orthogonal frequency division multiplexing with code-frequency index modulation (PC-CFIM) scheme, designed to enhance spectral efficiency (SE) while improving error performance. At the transmitter, PC-CFIM divides the information bits into two subsets. One subset is utilized for selecting the spreading code index, and the other is utilized for polar coded OFDM with index modulation (PC-OFDM-IM). In the proposed PC-CFIM framework, the polar-coded sequence is spread using the indices from code domain index modulation. At the receiver, the system employs code index selection coupled with polar decoding to ensure accurate retrieval of information bits. The integration of polar code with hybrid index modulation significantly improves interference resilience, thereby reducing bit error rates (BER). Moreover, the transmission of additional bits via the spreading code index further enhances the system’s SE. Simulation results show that compared to the conventional PC-OFDM-IM, the proposed PC-CFIM significantly improves the BER performance with enhanced SE.

关键词： Codes Spectral efficiency Transmitters OFDM Simulation Bit error rate Modulation Receivers Indexes Polar codes

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Congestion control of Multi-layer Cellular Networks based on Modeling of Transmit Power 3

Congestion Control of Multi-layer Cellular Networks based on...

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2020 3rd International Conference on Modeling, Simulation and Optimization Technologies and Applications, MSOTA 2020

作者： Dai, Jiahao Chen, Yongqun Chen, Yucheng Meng, Aodong Science and Technology on Communication Information Security Control Laboratory China China Electronic Group Corporation NO.36 Institute Zhejiang Jiaxing China

The explosive growth of network traffic and the limited storage node resources make the existing network architecture bear great pressure, and network congestion appears in work and life from time to time. In order to ensure the timeliness and effectiveness of the network, we propose a congestion control method based on transmission power. Different from previous work, we built a multi-layer cellular network consisting of multiple macro stations, small base stations and mobile terminals. On this basis, we establish a congestion control model based on the mixed queuing model of service window and calculate the input/output rate and congestion. Finally, we use simulation to verify the effectiveness of the congestion model. The network builder can use our model to set the appropriate power of macro stations and small base stations to ensure network stability. © Published under licence by IOP Publishing Ltd.

关键词： Base stations

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Lateral Movement Detection via Time-aware Subgraph Classification on Authentication Logs

arXiv

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arXiv 2024年

作者： Zhou, Jiajun Yao, Jiacheng Chen, Xuanze Yu, Shanqing Xuan, Qi Yang, Xiaoniu Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Binjiang Institute of Artificial Intelligence ZJUT Hangzhou310056 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou310023 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

Lateral movement is a crucial component of advanced persistent threat (APT) attacks in networks. Attackers exploit security vulnerabilities in internal networks or IoT devices, expanding their control after initial infiltration to steal sensitive data or carry out other malicious activities, posing a serious threat to system security. Existing research suggests that attackers generally employ seemingly unrelated operations to mask their malicious intentions, thereby evading existing lateral movement detection methods and hiding their intrusion traces. In this regard, we analyze host authentication log data from a graph perspective and propose a multi-scale lateral movement detection framework called LMDetect. The main workflow of this framework proceeds as follows: 1) Construct a heterogeneous multigraph from host authentication log data to strengthen the correlations among internal system entities;2) Design a time-aware subgraph generator to extract subgraphs centered on authentication events from the heterogeneous authentication multigraph;3) Design a multi-scale attention encoder that leverages both local and global attention to capture hidden anomalous behavior patterns in the authentication subgraphs, thereby achieving lateral movement detection. Extensive experiments on two real-world authentication log datasets demonstrate the effectiveness and superiority of our framework in detecting lateral movement behaviors. Copyright © 2024, The Authors. All rights reserved.

关键词： Network intrusion

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Simultaneous Localization and Recognition of Subwavelength Non-Cooperative Entities Based on SISO Time Reversal and Neural Networks

arXiv

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arXiv 2024年

作者： Wang, Yinchen Duan, Yu Ye, Yuqi Wang, Ren Li, Biao Jiang, Bin Liu, Xin Wang, Bingzhong Institute of Applied Physics University of Electronic Science and Technology of China Chengdu611731 China Communication Information Security Control Laboratory No. 36 Research Institute of CETC Jiaxing314033 China

The simultaneous localization and recognition of subwavelength non-cooperative entities within complex multi-scattering environments using a simplified system continues to pose a substantial challenge. In this paper, we address this challenge by synergistically integrating time reversal time-frequency phase prints (TRTFPPs) and neural networks. Initially, a time reversal (TR) single-input single-output (SISO) framework is employed to generate TRTFPPs. To enhance the models’ adaptability, particularly in the presence of noise, data augmentation techniques are applied. Subsequently, neural networks are employed to comprehend the TRTFPPs. Specifically, a cascaded neural network structure is embraced, encompassing both a recognition neural network and distinct neural networks for localizing different entities. Through the devised approach, two types of subwavelength entities are successfully identified and precisely localized through numerical simulations and experimental verification in laboratory environment. The proposed methodology holds applicability across various electromagnetic systems, including but not limited to detection, imaging, human-computer interaction, and the Internet of Things (IoT). Copyright © 2024, The Authors. All rights reserved.

关键词： Internet of things

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Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision

arXiv

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arXiv 2024年

作者： Jin, Chengxiang Zhou, Jiajun Xie, Chenxuan Yu, Shanqing Xuan, Qi Yang, Xiaoniu Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology Hangzhou310023 China Binjiang Institute of Artificial Intelligence ZJUT Hangzhou310056 China Institute of Cyberspace Security College of Computer Science and Technology Zhejiang University of Technology Hangzhou310023 China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

he rampant fraudulent activities on Ethereum hinder the healthy development of the blockchain ecosystem, necessitating the reinforcement of regulations. However, multiple imbalances involving account interaction frequencies and interaction types in the Ethereum transaction environment pose significant challenges to data mining-based fraud detection research. To address this, we first propose the concept of meta-interactions to refine interaction behaviors in Ethereum, and based on this, we present a dual self-supervision enhanced Ethereum fraud detection framework, named Meta-IFD. This framework initially introduces a generative self-supervision mechanism to augment the interaction features of accounts, followed by a contrastive self-supervision mechanism to differentiate various behavior patterns, and ultimately characterizes the behavioral representations of accounts and mines potential fraud risks through multi-view interaction feature learning. Extensive experiments on real Ethereum datasets demonstrate the effectiveness and superiority of our framework in detecting common Ethereum fraud behaviors such as Ponzi schemes and phishing scams. Additionally, the generative module can effectively alleviate the interaction distribution imbalance in Ethereum data, while the contrastive module significantly enhances the framework’s ability to distinguish different behavior patterns. The source code will be available in https://***/GISec-Team/Meta-IFD. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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IMPROVED GNSS-IR HEIGHT MEASUREMENT METHOD BASED ON LOCALLY WEIGHTED REGRESSION 9

IMPROVED GNSS-IR HEIGHT MEASUREMENT METHOD BASED ON LOCALLY ...

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9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Luo, Zhaowang Shang, Junna Li, Fangzhou Pang, Run Wang, Yiteng College of Telecommunication Engineering Hangzhou Dianzi University Hangzhou310018 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China

ISBN: (纸本)9781839538391

Global Navigation Satellite System Interferometric reflectance measurement (GNSS-IR) is a new remote sensing technology which uses satellite reflectance signals for monitoring. Aiming at the problems that the current GNSS-IR altimetry in land scenes is rarely applied and the accuracy of the traditional method is low under the reflection surface with high roughness, the traditional GNSS-IR altimetry is improved based on the local weighted regression method. A general navigation receiver method is proposed here, and does not need to use expensive special receiver or geodesic receiver. The local weighted regression method is used to separate the reflected signals to solve the problem of low local fitting accuracy of traditional methods when dealing with complex SNR changes in land scenes. The normalized Lomb-Scargle is used for spectrum analysis to improve the stability when there are few valid observations. The simulation and test results show that the proposed method has a significant improvement in the measurement accuracy compared with the traditional GNSS-IR method in the high-roughness ground scene. The single satellite measurement accuracy can reach within 10cm, and the root mean square error of the dual-frequency and multi-satellite combined altimetry measurement result is 2.62cm. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Reflection

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Towards Privacy-Preserving Cloud Storage:A Blockchain Approach

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Computers, Materials & Continua 2021年第12期69卷 2903-2916页

作者： Jia-Shun Zhang Gang Xu Xiu-Bo Chen Haseeb Ahmad Xin Liu Wen Liu Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China School of Information Science and Technology North China University of TechnologyBeijing100144China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan Inner Mongolia University of Science&Technology School of Information EngineeringBaotou014010China State Key Laboratory of Media Convergence and Communication Communication University of China School of Computer Science and Cybersecurity Communication University of China Key Laboratory of Convergent Media and Intelligent Technology Communication University of China Ministry of EducationBeijing102204China

With the rapid development of cloud computing technology,cloud services have now become a new business model for information *** cloud server provides the IT resources required by customers in a selfservice manner through the network,realizing business expansion and rapid ***,due to the insufficient protection of data privacy,the problem of data privacy leakage in cloud storage is threatening cloud *** address the problem,we propose BC-PECK,a data protection scheme based on blockchain and public key searchable ***,all the data is protected by the encryption *** privacy data is encrypted and stored in a cloud server,while the ciphertext index is established by a public key searchable encryption scheme and stored on the ***,based on the characteristics of trusted execution of smart contract technology,a control mechanism for data accessing and sharing is *** transaction is automatically recorded on the blockchain,which is fairer under the premise of ensuring the privacy and security of the data sharing ***,we analyzed the security and fairness of the current *** the comparison with similar schemes,we have shown the advantages of the proposed scheme.

关键词： Blockchain privacy protection smart contract public encryption keyword search

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ALFLAT: Chinese NER Using ALBERT, Flat-Lattice Transformer, Word Segmentation and Entity Dictionary 2nd

ALFLAT: Chinese NER Using ALBERT, Flat-Lattice Transformer, ...

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2nd EAI International Conference on Applied Cryptography in Computer and communications, AC3 2022

作者： Lv, Haifeng Ding, Yong School of Data Science and Software Engineering Wuzhou University Wuzhou China Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China

ISBN: (纸本)9783031170805

Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, one hand, since the lattice structure is dynamic and complex, although some existing lattice-based models are effectively utilize the parallel computation of GPUs, they do not fully utilize word segmentation boundary tags that as features are helpful for NER task. On the other hand, the character-word vector needs to be trained, and the user-defined entity dictionary cannot be effectively used. In this paper, we propose ALFLAT: based on a flat-lattice Transformer to incorporate ALBERT pre-trained model, word segmentation information and user-defined entity dictionary for Chinese NER. ALFLAT converts the lattice structure into a flat structure consisting of spans, integrate word segmentation embedding with the output of flat-lattice Transformer model, then modifies the emission scores according to the user-defined entity dictionary, finally utilize Viterbi decoding of the CRF layer to obtain the correct entity results. Each span corresponds to a character or latent word and its position in the original lattice. With the power of ALBERT pre-trained model, Transformer and position encoding, ALFLAT can fully leverage the lattice, word segmentation and user-defined entity dictionary information. Experiments on MSRA dataset show ALFLAT outperforms other lexicon-based models in performance and efficiency. © 2022, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Computational linguistics

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