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2024 OES China Ocean Acoustics, COA 2024

作者： Song, Zhenting Dong, Yang Zhan, Jiankang Shi, Zhanfei Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology China Harbin Engineering University Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350340297

To clarify the propagation mechanism and characteristics of lateral waves, in this paper, the wavenumber-integration method was used to establish a time-domain numerical model of shallow waveguide. The influence of lateral waves is often ignored in the calculation of the far-field sound field, as the near-distance lateral waves travel at the speed of seabed sound speed. For this reason, lateral waves arrive faster than direct waves at some distant locations. The model was used to simulate and analyze the time-range relationship between multi-path arrival structures in shallow-water waveguides. Finally, he seawater sound velocity, seawater depth, and sediment sound velocity of the experimental sea area were obtained via the processing and analysis of multichannel seismic exploration data. © 2024 IEEE.

关键词： Acoustic wave velocity

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A Comparative Study of IMM Kalman Filters and Neural Computing for Underwater Bearing Only Target Motion Analysis 21

A Comparative Study of IMM Kalman Filters and Neural Computi...

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21st International Bhurban Conference on Applied Sciences and technology, IBCAST 2024

作者： Ali, Wasiq Gang, Qiao Shah, Syed Asim College of Underwater Acoustic Engineering Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology Harbin150001 China College of Information and Communication Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798331516680

Bearing only target motion analysis (BOTMA) is essential for tracking and locating underwater targets, particularly in situations when conventional approaches such as range-based observations are not feasible or accessible. This paper offers a comparative investigation of interacting multiple model (IMM) Kalman filters and neural computing modelling for analyzing the motion of a target in underwater environment using only bearing data. The study aims to assess the effectiveness of above methods in efficiently analyzing motion features of an underwater target using just bearing observations obtained from two passive observers. The proposed methodologies address the challenges given by noisy and limited bearings, providing a substantial improvement in the analysis of the target's motion. To determine the performance of these two adaptive approaches, a supervised large turning track is developed for an underwater maneuvering target. Real time position, velocity, and turning features of a passive object are estimated in a cluttered marine atmosphere. The objective is to minimize the mean square error (MSE) among true and estimated motion of the target. The performance of each technique is evaluated on the basis of accuracy and resilience through detailed analysis. The results clearly demonstrate superiority of neural computing modelling compared to typical nonlinear filtering tools, like interacting multiple model extended Kalman filter (IMMEKF) and interacting multiple model unscented Kalman filter (IMMUKF). Therefore, this comparative study offers useful insights into the merits and drawbacks of each method, providing recommendations for future advancements in underwater target motion analysis and tracking models. © 2024 IEEE.

关键词： Extended Kalman filters

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The Sensitive Properties of Hydrate Reservoirs Based on Seismic Stereoscopic Detection technology

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Acta Geologica Sinica(English Edition) 2020年第2期94卷 530-544页

作者： LIU Xueqin XING Lei QIN Zhiliang LIU Huaishan Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001China Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001China College of Underwater Acoustic Engineering.Harbin Engineering University Harbin 150001China Key Lab of Submarine Geosciences and Prospecting Techniques MOE and College of Marine GeosciencesOcean University of ChinaQingdao 266100China Evaluation and Detection Technology Laboratory of Marine Mineral Resources Qingdao 266100China National Laboratory for Marine Science and Technology Qingdao 266061China

Higher-precision determinations of hydrate reservoirs, hydrate saturation levels and storage estimations are important for guaranteeing the ability to continuously research, develop and utilize natural gas hydrate resources in China. With seismic stereoscopic detection technology, which fully combines the advantages of different seismic detection models, hydrate formation layers can be observed with multiangle, wide-azimuth, wide-band data with a high precision. This technique provides more reliable data for analyzing the distribution characteristics of gas hydrate reservoirs, establishing velocity models, and studying the hydrate-sensitive properties of petrophysical parameters;these data are of great significance for the exploration and development of natural gas hydrate resources. Based on a velocity model obtained from the analysis of horizontal streamer velocity data in the hydrate-bearing area of the Shenhu Sea, this paper uses three VCs(longitudinal spacing of 25 m) and four OBSs(transverse spacing of 200 m) to jointly detect seismic datasets consisting of wave points based on an inversion of traveltime imaging sections. Accordingly, by comparing the differences between the seismic phases in the original data and the forward-modeled seismic phases, multiangle coverage constraint corrections are applied to the initial velocity model, and the initial model is further optimized, thereby improving the imaging quality of the streamer data. Petrophysical elastic parameters are the physical parameters that are most directly and closely related to rock formations and reservoir physical properties. Based on the optimized velocity model, the rock elastic hydrate-sensitive parameters of the hydrate reservoirs in the study area are inverted, and the sensitivities of the petrophysical parameters to natural gas hydrates are investigated. According to an analysis of the inversion results obtained from these sensitive parameters, λρ, Vp and λμ are simultaneously controlled b

关键词： natural gas hydrate stereoscopic detection elastic modulus sensitive parameters

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Research on the Cross-Correlation Characteristics of Signals from Ocean Bottom Seismometer

Research on the Cross-Correlation Characteristics of Signals...

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2024 OES China Ocean Acoustics, COA 2024

作者： Cao, Dejin Zhang, Haigang Xie, Jinhuai Gao, Xiao College of Underwater Acoustic Engineering Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology Key Lab. of Mar. Info. Acquisition and Security of Ministry of Industry and Information Technology Harbin China

ISBN: (纸本)9798350340297

In this study, considerable differences in waveform between vector signals and acoustic pressure signals were received from the seabed interface. The cross-correlation characteristics between the acoustic pressure and particle velocity signals received via an ocean bottom seismometer were analyzed using experimental data obtained from very low-frequency sound propagation experiments conducted in the South China Sea area. On th basis of the spectral element method, the correlation coefficient of the pressure and particle velocity signals in seawater and seabed interface was simulated and compared with experimental data to validate the cross-correlation characteristics at the seabed interface. Finally, the correlation coefficients between pressure and particle velocity in different types of seabed environments were analyzed. The results reveal that the elastic characteristics of the seabed can have a certain impact on the cross-correlation characteristics of the pressure and particle velocity signals received by an ocean bottom seismometer, which results in a relatively small cross-correlation coefficient between the seabed interface acoustic pressure and horizontal particle velocity signals. © 2024 IEEE.

关键词： Image segmentation

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Study of the strength characteristics of particle velocity at the seabed interface

Study of the strength characteristics of particle velocity a...

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2023 International Conference on Frontiers of Ocean Science and technology, ICFOST 2023

作者： Xie, Jinhuai Cao, Dejin Zhang, Haigang National Key Laboratory of Underwater Acoustic Technology Harbin Engineering University Harbin China Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology Harbin Engineering University Harbin China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China

When studying the propagation characteristics of the acoustic vector field, the law that the horizontal particle velocity intensity is stronger than the vertical particle velocity intensity does not apply near the seabed interface. To verify this characteristic, a sea experiment was conducted in the South China Sea to obtain the long-range propagation data of particle velocity at the seabed interface. Then, based on the normal mode method, the particle velocity intensity distribution of different types of seabed is theoretically simulated and compared with the experimental data, and the intensity characteristics of particle velocity at the seabed interface are verified. The results show that the particle velocity strength of the elastic seabed is mainly influenced by the submarine shear wave, which leads to the phenomenon that the vertical particle velocity is stronger than the horizontal particle velocity strength, and the relative strength of the two is determined by the compression wave velocity, the shear wave velocity and the seabed density. © Published under licence by IOP Publishing Ltd.

关键词： Shear waves

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Passive Line Spectrum Detection of a Moving Target With the Fractional Fourier Transform

Passive Line Spectrum Detection of a Moving Target With the ...

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2024 OES China Ocean Acoustics, COA 2024

作者： Yuxin, Zhao Dajun, Sun Jidan, Mei Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology Harbin150001 China Ministry of Industry and Information Technology Key Laboratory of Marine Information Acquisition and Security Harbin150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798350340297

To detect line spectrum signals from underwater moving targets, a long-time-integral line spectrum detection method based on the fractional Fourier transform (FRFT) is proposed in this work. This method can mitigate the decrease in the gain of the line spectrum caused by the motion of a target and the resulting Doppler shift. By establishing a mathematical model of the received signal from a moving target, the polynomial characteristics of the phase of the received signal are deduced, and second-order approximate results are given. The polynomial phase signal parameters are related to the parameters of the moving target. Because FRFT can be applied to the integral processing of second-order polynomials, the corresponding processing model and method are given using the FRFT in this work. The actual gains associated with FFT and FRFT for moving targets with different velocities and frequencies are summarized and compared with the theoretical ones. Furthermore, the optimal integration time under different conditions is estimated. Compared with FFT, FRFT lengthens the integration time of the line spectrum of moving signals. The processed results from the simulation data show that this method has excellent line spectrum detection performance at a low SNR and can be adapted to complex situations such as multiple targets and multiple line spectrum signals. © 2024 IEEE.

关键词： Target tracking

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The optimal attack-defense scheme for secret sharing 15

The optimal attack-defense scheme for secret sharing

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart data, Smartdata 2022

作者： Ma, Juan Chen, Yuling Lv, Xiao Qian, Xiaobin Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang China Guilin University of Electronic Technology Guangxi Key Laboratory of Cryptography and Information Security Guilin China Weifang University of Science and Technology Blockchain Laboratory of Agricultural Vegetables Weifang China Guizhou Shuanhui Big Data Industry Development Co. Ltd Guiyang China Guizhou CoVision Science &technology Co. Ltd Guiyang China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

The attack-defense issue of secret sharing has been a pressing cryptography research need. For solving this issue, this study proposes an optimal secret-share attack-defense model with game theory and information theory. This study constructs an attack channel for attackers and a defense channel for defenders. Then, we propose a game model that utilizes mutual information to measure the attack and defensive capabilities of attackers and defenders. Next, this study proves that there is a Nash equilibrium in this game model by analyzing the strategies of each attacker/defender. Finally, we analyze the change of k value and attack and defensive capabilities. Moreover, we also prove the best attack and defensive strategies. © 2022 IEEE.

关键词： Game theory

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Deep Learning Algorithms Design and Implementation Based on Differential Privacy 3rd

Deep Learning Algorithms Design and Implementation Based on ...

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3rd International Conference on Machine Learning for Cyber security, ML4CS 2020

作者： Xu, Xuefeng Yao, Yanqing Cheng, Lei Key Laboratory of Aerospace Network Security Ministry of industry and information technology School of Cyberspace Science and Technology Beihang University Beijing100191 China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China Beijing Key Laboratory of Network Technology Beihang University Beijing China Shenzhen Research Institute of Big Data Shenzhen518000 China

ISBN: (纸本)9783030622220

Deep learning models bear the risks of privacy leakage. Attackers can obtain sensitive information contained in training data with some techniques. However, existing differentially private methods such as Differential Privacy-Stochastic Gradient Descent (DP-SGD) and Differential Privacy-Generative Adversarial Network (DP-GAN) are not very efficient as they require to perform sampling multiple times. More importantly, DP-GAN algorithm need public data to set gradient clipping threshold. In this paper, we introduce our refined algorithms to tackle these problems. First, we employ random shuffling instead of random sampling to improve training efficiency. We also test Gaussian and Laplace Mechanisms for clipping gradients and injecting noise. Second, we employ zero Concentrated Differential Privacy (zCDP) to compute overall privacy budget. Finally, we adopt dynamical gradient clipping in DP-GAN algorithm. During each iteration, we random sample training examples and set the average gradients norm as the new threshold. This not only makes the algorithm more robust but also doesn’t increase the overall privacy budget. We experiment with our algorithms on MNIST data sets and demonstrate the accuracies. In our refined DP-SGD algorithm, we achieve test accuracy of 96.58%. In our refined DP-GAN algorithm, we adopt the synthetic data to train models and reach test accuracy of 91.64%. The results show that our approach ensures model usability and provides the capability of privacy protection. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Decode the Dark Side of the Language: Applications of LLMs in the Dark Web 9

Decode the Dark Side of the Language: Applications of LLMs i...

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9th IEEE International Conference on data Science in Cyberspace, DSC 2024

作者： Chen, Hongfan Diao, Yigang Xiang, Hui Huo, Yixuan Xie, Xiaqing Zhao, Jiapeng Wang, Xuebin Sun, Yanwei Shi, Jinqiao Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing China Zhejiang University The State Key Laboratory of Blockchain and Data Security Hangzhou China Beijing China Data and Technology Support Center Cyberspace Administration of China Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China

ISBN: (纸本)9798350391367

Previous studies have discovered that Transformers pre-trained on large scale datasets have a great advantage over traditional methods and can achieve human-level performance in many NLP tasks. Various encoder-only models like BERT and RoBERTa are used in the researches of the language in the Dark Web and most of them have achieved state-of-the-art performance. However, decoder-only models are not frequently used as they were considered to be unsuitable for NLU tasks until recent advancements in large language models. In this paper, we discuss the application of large scale decoder-only models in NLP tasks of real-world Dark Web research. We explore the capabilities of these models with the most realistic datasets in this specific domain. Surprisingly, results show that decoder-only models can achieve similar or better performance compared with state-of-the-art encoder-only model in some cases and show their own unique advantages in such field. We also discuss the limitations of these models and the challenges associated with their application in such field. Our study unveils the potential of decoder-only models in NLP tasks of real-world Dark Web research. © 2024 IEEE.

关键词： Decoding

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A Multipath Source Location Privacy Protection Scheme in Wireless Sensor Networks via Proxy Node 15

A Multipath Source Location Privacy Protection Scheme in Wir...

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作者： Sun, Jing Chen, Yuling Lv, Xiao Qian, Xiaobin Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang China Guilin University of Electronic Technology Guangxi Key Laboratory of Cryptography and Information Security Guilin China Weifang University of Science and Technology Blockchain Laboratory of Agricultural Vegetables Weifang China Guizhou Shuanhui Big Data Industry Development Co.Ltd Guiyang China Guizhou CoVision Science &technology Co.Ltd Guiyang China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

Wireless sensor networks (WSNs) are widely devoted to monitoring target. Attackers can detect the source node by hop-by-hop backtracking strategy. Therefore, it is necessary to protect the location privacy of data source nodes. Source location privacy (SLP) plays a crucial role in WSNs security. To ensure the security of source location in WSNs, a multi-path source location privacy protection scheme via proxy node is proposed. Source node initiates restricted flooding and directed routing algorithm keep packets away from the source location, effectively increasing the number of random directed paths. Greedy quantitative routing is the basis of generating vast quantities of relay nodes with diverse geographical locations. The receiving node randomly generates angles to complete equal-hop routing. The sending node continuously selects any near-neighbor node as a participant until the data packet is sent to the spin node. The spin node chooses the adjacent quadrant to complete the variable length equal-hop routing through proxy nodes and forwards the packet to the sink node. Theoretical analysis and simulation experiments show that this scheme provides excellent privacy for the source location. © 2022 IEEE.

关键词： data privacy

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