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Digital twin modeling and controlling of optical power evolution enabling autonomous-driving optical networks: a Bayesian approach

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Advanced Photonics 2024年第2期6卷 69-80页

作者： Xiaomin Liu Yihao Zhang Yuli Chen Yichen Liu Meng Cai Qizhi Qiu Mengfan Fu Lilin Yi Weisheng Hu Qunbi Zhuge Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and NetworksDepartment of Electronic Engineering

Optical networks are evolving toward ultrawide bandwidth and autonomous operation. In this scenario, it is crucial to accurately model and control optical power evolutions(OPEs) through optical amplifiers(OAs), as they directly affect the signal-to-noise ratio and fiber nonlinearities. However, a fundamental contradiction arises between the complex physical phenomena in optical transmission and the required precision in network control. Traditional theoretical methods underperform due to ideal assumptions, while data-driven approaches entail exorbitant costs associated with acquiring massive amounts of data to achieve the desired level of accuracy. In this work, we propose a Bayesian inference framework(BIF) to construct the digital twin of OAs and control OPE in a data-efficient manner. Only the informative data are collected to balance the exploration and exploitation of the data space, thus enabling efficient autonomous-driving optical networks(ADONs). Simulations and experiments demonstrate that the BIF can reduce the data size for modeling erbium-doped fiber amplifiers by 80% and Raman amplifiers by 60%. Within 30 iterations, the optimal controlling performance can be achieved to realize target signal/gain profiles in links with different types of OAs. The results show that the BIF paves the way to accurately model and control OPE for future ADONs.

关键词： optical fiber communications digital twin Bayesian inference optical amplifiers autonomous-driving optical networks

Silicon photonic integrated interrogator for fiber-optic distributed acoustic sensing

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Photonics Research 2024年第3期12卷 465-473页

作者： ZHICHENG JIN JIAGENG CHEN YANMING CHANG QINGWEN LIU ZUYUAN HE State Key Laboratory of Advanced Optical Communication System and networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Distributed acoustic sensing(DAS)technology has been a promising tool in various ***,the large size and relatively high cost of DAS equipment composed of discrete devices restrict its further popularization to some degree,and the photonic integration technology offers a potential *** this paper,we demonstrate an integrated interrogator for DAS on the silicon-on-insulator(SOI)*** design of the chip revolves around a Mach–Zehnder modulator(MZM)transmitter and a dual-quadrature and dualpolarization coherent *** integrated interrogator supports multiple DAS schemes,including the time-gated digital optical frequency domain reflectometry(TGD-OFDR),which is adopted for system performance evaluation.59■strain resolution in 12.1km sensing fiber with 1.14 m spatial resolution(SR)is ***,along 49.0 km sensing fiber,81■strain resolution with 3.78 m SR is *** results show that the integrated interrogator has comparable performance to the discrete DAS *** the best of our knowledge,this is the first dedicated on-chip DAS interrogator,which validates the effectiveness of the blend of photonics integration and DAS technology.

关键词： fiber polarization modulator

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Integrated optical frequency transfer and optical physical layer key distribution with enhanced link reciprocity detection

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Science China(Information Sciences) 2024年第7期67卷 335-336页

作者： Kunfeng XIE Liang HU Jianping CHEN Guiling WU State Key Laboratory of Advanced Optical Communication System and networks Department of Electronic EngineeringShanghai Jiao Tong University

Optical fiber transmission has been widely used in communications and metrology, wherein optical frequency transfer (OFT) and optical physical layer secure key distribution (OKD) have become research hotspots [1, 2]. Moreover,OFT can perform a comparison between state-of-the-art optical atomic clocks and implement coherent optical phase transfer over long distances to support geodesy [1, 3].

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FMSA:a meta-learning framework-based fast model stealing attack technique against intelligent network intrusion detection systems

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Cybersecurity 2024年第1期7卷 110-121页

作者： Kaisheng Fan Weizhe Zhang Guangrui Liu Hui He School of Cyberspace Science Harbin Institute of TechnologyHarbin 150001China department of New networks Peng Cheng LaboratoryShenzhen 518055GuangdongChina

Intrusion detection systems are increasingly using machine *** machine learning has shown excellent performance in identifying malicious traffic,it may increase the risk of privacy *** paper focuses on imple-menting a model stealing attack on intrusion detection *** model stealing attacks are hard to imple-ment in practical network environments,as they either need private data of the victim dataset or frequent access to the victim *** this paper,we propose a novel solution called Fast Model Stealing Attack(FMSA)to address the problem in the field of model stealing *** also highlight the risks of using ML-NIDS in network ***,meta-learning frameworks are introduced into the model stealing algorithm to clone the victim model in a black-box ***,the number of accesses to the target model is used as an optimization term,resulting in minimal queries to achieve model ***,adversarial training is used to simulate the data distribution of the target model and achieve the recovery of privacy *** experiments on multiple public datasets,compared to existing state-of-the-art algorithms,FMSA reduces the number of accesses to the target model and improves the accuracy of the clone model on the test dataset to 88.9%and the similarity with the target model to 90.1%.We can demonstrate the successful execution of model stealing attacks on the ML-NIDS system even with protective measures in place to limit the number of anomalous queries.

关键词： AI security Model stealing attack Network intrusion detection Meta learning

Analog spatiotemporal feature extraction for cognitive radio-frequency sensing with integrated photonics

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Light(Science & Applications) 2024年第3期13卷 478-487页

作者： Shaofu Xu Binshuo Liu Sicheng Yi Jing Wang Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina

Analog feature extraction(AFE)is an appealing strategy for low-latency and efficient cognitive sensing systems since key features are much sparser than the Nyquist-sampled ***,applying AFE to broadband radio-frequency(RF)scenarios is challenging due to the bandwidth and programmability bottlenecks of analog electronic ***,we introduce a photonics-based scheme that extracts spatiotemporal features from broadband RF signals in the analog *** feature extractor structure inspired by convolutional neural networks is implemented on integrated photonic circuits to process RF signals from multiple antennas,extracting valid features from both temporal and spatial *** of the tunability of the photonic devices,the photonic spatiotemporal feature extractor is trainable,which enhances the validity of the extracted ***,a digital-analog-hybrid transfer learning method is proposed for the effective and low-cost training of the photonic feature *** validate our scheme,we demonstrate a radar target recognition task with a 4-GHz instantaneous *** results indicate that the photonic analog feature extractor tackles broadband RF signals and reduces the sampling rate of analog-to-digital converters to 1/4 of the Nyquist sampling while maintaining a high target recognition accuracy of 97.5%.Our scheme offers a promising path for exploiting the AFE strategy in the realm of cognitive RF sensing,with the potential to contribute to the efficient signal processing involved in applications such as autonomous driving,robotics,and smart factories.

关键词： scheme driving smart

Low-modal-crosstalk doped-fiber amplifiers in few-mode-fiber-based systems

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Photonics Research 2024年第08期12卷 1768-1775页

作者： SHUAILUO HUANG LEI SHEN GANG QIAO YUANPENG DING YUYANG GAO JIAN CUI BAOLONG ZHU SIYUAN LIU MINGQING ZUO JINGLONG ZHU LEI ZHANG JIE LUO YONGQI HE ZHANGYUAN CHEN JUHAO LI State Key Laboratory of Advanced Optical Communication Systems and networks Peking University State Key Laboratory of Optical Fiber and Cable Manufacture Technology Yangtze Optical Fibre and Cable Joint Stock Limited Company School of Computer and Communication Engineering University of Science and Technology Beijing department of networks China Mobile Communications Group Co. Ltd. department of Fundamental Network Technology China Mobile Research Institute Pengcheng Laboratory

Independent light propagation through one or multiple modes is commonly considered as a basic demand for mode manipulation in few-mode fiber（FMF）-or multimode fiber（MMF）-based optical systems such as transmission links, optical fiber lasers, or distributed optical fiber sensors. However, the insertion of doped-fiber amplifiers always kills the entire effort by inducing significant modal crosstalk. In this paper, we propose the design of doped-fiber amplifiers in FMF-based systems adopting identical multiple-ring-core（MRC） index profiles for both passive and doped fibers to achieve low modal crosstalk. We develop the direct-glass-transition（DGT） modified chemical vapor deposition（MCVD） processing for precise fabrication of few-mode erbium-doped fibers（FM-EDFs） with MRC profiles of both refractive index and erbium-ion doping distribution. Then, a few-mode erbium-doped-fiber amplifier（FM-EDFA） with a maximum gain of 26.08 dB and differential modal gain（DMG） of 2.3 dB is realized based on fabricated FM-EDF matched with a transmission FMF supporting four linearly polarized（LP） modes. With the insertion of the FM-EDFA, 60 + 60 km simultaneous LP01∕LP11∕LP21∕LP02transmission without inter-modal multiple-input multiple-output digital signal processing（MIMO-DSP） is successfully demonstrated. The proposed design of low-modal-crosstalk doped-fiber amplifiers provides, to our knowledge, new insights into mode manipulation methods in various applications. ? 2024 Chinese Laser Press

关键词： Chemical vapor deposition Erbium fibers Few mode fibers High power fiber lasers Multimode fibers Signal processing

Rethinking multi-spatial information for transferable adversarial attacks on speaker recognition systems

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 620-631页

作者： Junjian Zhang Hao Tan Le Wang Yaguan Qian Zhaoquan Gu Guangzhou University GuangzhouChina department of New networks Peng Cheng LaboratoryShenzhenChina Harbin Institute of Technology(Shenzhen) ShenzhenChina Zhejiang University of Science and Technology HangzhouChina

Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical *** black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are *** by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against ***,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating *** reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve *** authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.

关键词： speaker recognition spoofing attacks

NFA:A neural factorization autoencoder based online telephony fraud detection

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Digital Communications and networks 2024年第1期10卷 158-167页

作者： Abdul Wahid Mounira Msahli Albert Bifet Gerard Memmi department of Computer Sciences and networks(INFRES) LTCITelecom ParisInstitut Polytechnique de ParisPalaiseau91120France Artificial Intelligence Institute The University of WaikatoPrivate Bag 31053240HamiltonNew Zealand

The proliferation of internet communication channels has increased telecom fraud,causing billions of euros in losses for customers and the industry each *** constantly find new ways to engage in illegal activity on the *** reduce these losses,a new fraud detection approach is *** fraud detection involves identifying a small number of fraudulent calls from a vast amount of call *** an effective strategy to combat fraud has become *** much effort has been made to detect fraud,most existing methods are designed for batch processing,not real-time *** solve this problem,we propose an online fraud detection model using a Neural Factorization Autoencoder(NFA),which analyzes customer calling patterns to detect fraudulent *** model employs Neural Factorization Machines(NFM)and an Autoencoder(AE)to model calling patterns and a memory module to adapt to changing customer *** evaluate our approach on a large dataset of real-world call detail records and compare it with several state-of-the-art *** results show that our approach outperforms the baselines,with an AUC of 91.06%,a TPR of 91.89%,an FPR of 14.76%,and an F1-score of 95.45%.These results demonstrate the effectiveness of our approach in detecting fraud in real-time and suggest that it can be a valuable tool for preventing fraud in telecommunications networks.

关键词： Telecom industry Streaming anomaly detection Fraud analysis Factorization machine Real-time system Security

Joint position optimization,user association,and resource allocation for load balancing in UAV-assisted wireless networks

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Digital Communications and networks 2024年第1期10卷 25-37页

作者： Daosen Zhai Huan Li Xiao Tang Ruonan Zhang Haotong Cao School of Electronics and Information Northwestern Polytechnical UniversityXian710072China State Key Laboratory of Integrated Services networks Xidian UniversityXian710071China department of Computing Hong Kong Polytechnic UniversityHong Kong SARChina

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum *** tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded *** fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent *** tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV ***,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation *** further propose an iterative power allocation algorithm based on the sequential convex approximation *** simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

关键词： Load balance Unmanned aerial vehicle Userassociation Resource management