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Street-Level IP Geolocation Algorithm Based on Landmarks Clustering

Computers, Materials & Continua 2021年第3期66卷 3345-3361页

作者： Fan Zhang Fenlin Liu Rui Xu Xiangyang Luo Shichang Ding Hechan Tian PLA Strategic Support Force Information Engineering University Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China Cyberspace Security Key Laboratory of Sichuan Province Chengdu610000China China Electronic Technology Cyber Security Co. Ltd.Chengdu610000China University of Goettingen Goettingen37075Germany

Existing IP geolocation algorithms based on delay similarity often rely on the principle that geographically adjacent IPs have similar ***,this principle is often invalid in real Internet environment,which leads to unreliable geolocation *** improve the accuracy and reliability of locating IP in real Internet,a street-level IP geolocation algorithm based on landmarks clustering is ***,we use the probes to measure the known landmarks to obtain their delay vectors,and cluster landmarks using ***,the landmarks are clustered again by their latitude and longitude,and the intersection of these two clustering results is taken to form training ***,we train multiple neural networks to get the mapping relationship between delay and location in each training ***,we determine one of the neural networks for the target by the delay similarity and relative hop counts,and then geolocate the target by this *** it brings together the delay and geographical coordinates clustering,the proposed algorithm largely improves the inconsistency between them and enhances the mapping relationship between *** evaluate the algorithm by a series of experiments in Hong Kong,Shanghai,Zhengzhou and New *** experimental results show that the proposed algorithm achieves street-level IP geolocation,and comparing with existing typical streetlevel geolocation algorithms,the proposed algorithm improves the geolocation reliability significantly.

关键词： IP geolocation neural network landmarks clustering delay similarity relative hop

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Analysis of Instantaneous Angular Speed Accuracy Considering Encoder Errors

Analysis of Instantaneous Angular Speed Accuracy Considering...

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International Conference on Automation and computing (ICAC)

作者： Yuanhao Liu Fengshou Gu Qiang Zeng State Key Laboratory of Mechanical Transmissions for Advanced Equipment Chongqing University Chongqing China School of Computing and Engineering University of Huddersfield Huddersfield UK

ISBN: (数字)9798350360882

ISBN: (纸本)9798350360899

Instantaneous Angular Speed (IAS) is closely related to the dynamic behavior of rotating machinery and plays a crucial role in diagnosing faults. However, the measurement of the IAS is subject to various errors inevitably, which directly affect the accuracy of IAS estimation and diminish the precision of fault diagnosis in rotating machinery. Currently, the estimation of IAS primarily relies on time counting methods, and there has been limited research conducted on the application of Frequency Domain Demodulation (FDD) as an IAS estimation method, despite its potential for providing lower noise levels. The study of IAS errors based on the FFD method has received even less attention. This study undertakes pertinent research and investigates the issue identified. Firstly, it develops a model for IAS estimation using FDD, considering the specific characteristics of the encoder disk signal. Secondly, it establishes IAS models for eccentric and inclined encoder disks, considering the spatial geometric characteristics associated with different types of encoder disk errors. In conclusion, the experimental results successfully validate the accuracy and validity of the proposed theoretical models. This study lays a theoretical foundation for the precise measurement of IAS, thereby enhancing the reliability of using IAS for condition monitoring in rotating machinery.

关键词： Fault diagnosis Accuracy Frequency-domain analysis Measurement uncertainty Estimation Machining Reliability theory Machinery Rotation measurement Noise level

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Self-Dual Hadamard Bent Sequences

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Journal of Systems Science & Complexity 2023年第2期36卷 894-908页

作者： SHI Minjia LI Yaya CHENG Wei CRNKOVIC Dean KROTOV Denis SOLéPatrick Key Laboratory of Intelligent Computing Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security(Institute of Information Engineering) Chinese Academy of SciencesBeijing 100093China. LTCI Télécom ParisParis91120 PalaiseauFrance Secure-IC S.A.S. 104 Bd du Montparnasse75014 Paris Faculty of Mathematics University of RijekaNovosibirsk 630090Russia Sobolev Institute of Mathematics Novosibirsk 630090Russia Aix Marseille Univ CNRSCentrale MarseilleI2MMarseilleFrance

A new notion of bent sequence related to Hadamard matrices was introduced recently,motivated by a security application(Solé,et al.,2021).The authors study the self-dual class in length at most *** authors use three competing methods of generation:Exhaustion,Linear Algebra and Gr?bner *** Hadamard matrices and Bush-type Hadamard matrices provide many *** authors conjecture that if v is an even perfect square,a self-dual bent sequence of length v always *** authors introduce the strong automorphism group of Hadamard matrices,which acts on their associated self-dual bent *** authors give an efficient algorithm to compute that group.

关键词： Bent sequences bush-type Hadamard matrices Hadanard matrices PUF functions regular Hadamard matrices

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Simulation detection based on single photon quantum key distribution protocol

Simulation detection based on single photon quantum key dist...

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2020 International Conference on Electronics, Communications and Information Technology, CECIT 2020

作者： Liu, X.N. Hu, C.C. Yin, M.J. Jin, L. School of Information Engineering Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China School of Cyberspace and Security Information Engineering University Zhengzhou China

With the continuous development of quantum communication in recent years, quantum key distribution (QKD) has also become a key technology in the field of quantum communication. Due to the limitation of physical resources and experimental conditions, the effectiveness of different communication protocols cannot be accurately analyzed. To solve this problem, a protocol simulation method is proposed, BB84 and B92 protocols are simulated and analyzed on a classic computer by this method. On the Eclipse IDE Developers platform, the simulation program of the quantum communication protocol was written using Java language, the simulation process under the ideal environment and the eavesdropping environment was analyzed with emphasis. The simulation results show that the key distribution efficiency of BB84 is about 50% without eavesdroppers, which is much higher than 25% of B92, and the key distribution efficiency under eavesdropping conditions is about 25% and 18%. The experimental results are consistent with theoretical expectations, verifying the correctness of the protocol simulation, and also proving the feasibility of using computers for quantum communication protocol simulation. © Published under licence by IOP Publishing Ltd.

关键词： Computer software

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An Adaptive Proximal Inexact Gradient Framework and Its Application to Per-Antenna Constrained Joint Beamforming and Compression Design

arXiv

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arXiv 2025年

作者： Fan, Xilai Jiang, Bo Liu, Ya-Feng State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing210023 China

In this paper, we propose an adaptive proximal inexact gradient (APIG) framework for solving a class of nonsmooth composite optimization problems involving function and gradient errors. Unlike existing inexact proximal gradient methods, the proposed framework introduces a new line search condition that jointly adapts to function and gradient errors, enabling adaptive stepsize selection while maintaining theoretical guarantees. Specifically, we prove that the proposed framework achieves an ϵ-stationary point within O(ϵ−2) iterations for nonconvex objectives and an ϵ-optimal solution within O(ϵ−1) iterations for convex cases, matching the best-known complexity in this context. We then custom-apply the APIG framework to an important signal processing problem: the joint beamforming and compression problem (JBCP) with per-antenna power constraints (PAPCs) in cooperative cellular networks. This customized application requires careful exploitation of the problem’s special structure such as the tightness of the semidefinite relaxation (SDR) and the differentiability of the dual. Numerical experiments demonstrate the superior performance of our custom-application over state-of-the-art benchmarks for the JBCP. © 2025, CC BY.

关键词： Beamforming

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Dual-axial self-attention network for text classification

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Science China(Information Sciences) 2021年第12期64卷 80-90页

作者： Xiaochuan ZHANG Xipeng QIU Jianmin PANG Fudong LIU Xingwei LI State Key Laboratory of Mathematical Engineering and Advanced Computing Shanghai Key Laboratory of Intelligent Information Processing Fudan University School of Computer Science Fudan University

Text classification is an important task in natural language processing and numerous studies aim to improve the accuracy and efficiency of text classification models. In this study, we propose an effective and efficient text classification model which is based on self-attention solely. The recently proposed multidimensional self-attention significantly improved the performance of self-attention. However, existing models suffer from two major limitations:(1) the previous multi-dimensional self-attention models are quite timeconsuming;(2) the dependencies of elements along the feature axis are not taken into account. To overcome these problems, in this paper, a much more computational efficient multi-dimensional self-attention model is proposed, and two parallel self-attention modules, called dual-axial self-attention, are applied to capture rich dependencies along the feature axis as well as the text axis. A text classification model is then *** experimental results on eight representative datasets show that the proposed text classification model can obtain state-of-the-art results and the proposed self-attention outperforms conventional self-attention models.

关键词： text classification dual-axial self-attention feature-axial dependency

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A Software Diversity-Based Lab in Operating System for Cyber Security Students 3

A Software Diversity-Based Lab in Operating System for Cyber...

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3rd IEEE International Conference on Computer Science and Educational Informatization, CSEI 2021

作者： Wang, Junchao Pang, Jianmin Shan, Zheng Wei, Jin Yao, Jinyang Liu, Fudong State Key Laboratory of Mathematical Engineering and Advanced Computing Zheng Zhou China School of Computer Science Data Arena Institute Fudan University Zheng Zhou China

ISBN: (纸本)9781728184739

The course of operating system's labs usually fall behind the state of art technology. In this paper, we propose a Software Diversity-Assisted Defense (SDAD) lab based on software diversity, mainly targeting for students majoring in cyber security and computer science. This lab is consisted of multiple modules and covers most of the important concepts and principles in operating systems. Thus, the knowledge learned from the theoretical course will be deepened with the lab. For students majoring in cyber security, they can learn this new software diversity-based defense technology and understand how an exploit works from the attacker's side. The experiment is also quite stretchable, which can fit all level students. © 2021 IEEE.

关键词： Students

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Stepwise DOA Estimation for Coherent and Uncorrelated Mixed Signals on Coprime Array

Stepwise DOA Estimation for Coherent and Uncorrelated Mixed ...

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IEEE advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)

作者： Heng Jiang Lichun Li Hailong Zhang Hongyi Pan Xue Li College of Information System Engineering Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665479691

The coprime array constructs virtual array to obtain higher degrees of freedom (DOF), but the premise of doing so is that the signals are independent of each other. Once there are coherent signals, the signal model of virtual array is destroyed and the method fails. To solve these problems, we propose the stepwise estimation of the Direction of Arrival (DOA) for a mixture of coherent and uncorrelated signals. Firstly, the symmetry of the two coprime subarrays is used to eliminate the uncorrelated signals, and combined with the properties of prime numbers, the coherent source DOA is jointly estimated. The obtained coherent source DOA was combined with the optimization algorithm to remove the coherent signal in the mixed signal. Finally, the virtual domain signal processing method was used to estimate the independent source DOA. This method can effectively reduce the influence of coherent signals on the accuracy of DOA estimation without loss of degrees of freedom. In this paper, the feasibility of the proposed method is proved by theoretical derivation, and the effectiveness of the method is also verified by experimental simulations.

关键词： Direction-of-arrival estimation Automation Simulation Estimation Signal processing algorithms Interference Signal processing

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Multi-objective Firefly Algorithm for Test Data Generation with Surrogate Model 7th

Multi-objective Firefly Algorithm for Test Data Generation w...

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7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021

作者： Zhang, Wenning Zhou, Qinglei Jiao, Chongyang Xu, Ting State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China Zhongyuan University of Technology Zhengzhou450000 China Zhengzhou University Zhengzhou450000 China

ISBN: (纸本)9789811659393

To solve the emerging complex optimization problems, multi objective optimization algorithms are needed. By introducing the surrogate model for approximate fitness calculation, the multi objective firefly algorithm with surrogate model (MOFA-SM) is proposed in this paper. Firstly, the population was initialized according to the chaotic mapping. Secondly, the external archive was constructed based on the preference sorting, with the lightweight clustering pruning strategy. In the process of evolution, the elite solutions selected from archive were used to guide the movement to search optimal solutions. Simulation results show that the proposed algorithm can achieve better performance in terms of convergence iteration and stability. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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SUMI-IFL: An Information-Theoretic Framework for Image Forgery Localization with Sufficiency and Minimality Constraints 39

SUMI-IFL: An Information-Theoretic Framework for Image Forge...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Sheng, Ziqi Lu, Wei Luo, Xiangyang Zhou, Jiantao Cao, Xiaochun School of Computer Science and Engineering MoE Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University China State Key Laboratory of Mathematical Engineering and Advanced Computing China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau Macao School of Cyber Science and Technology Shenzhen Campus of Sun Yat-sen University China

ISBN: (纸本)157735897X

Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering technologies, extracting more comprehensive and accurate forgery clues remains an urgent challenge. To address these challenges, we introduce a novel information-theoretic IFL framework named SUMI-IFL that imposes sufficiency-view and minimality-view constraints on forgery feature representation. First, grounded in the theoretical analysis of mutual information, the sufficiency-view constraint is enforced on the feature extraction network to ensure that the latent forgery feature contains comprehensive forgery clues. Considering that forgery clues obtained from a single aspect alone may be incomplete, we construct the latent forgery feature by integrating several individual forgery features from multiple perspectives. Second, based on the information bottleneck, the minimality-view constraint is imposed on the feature reasoning network to achieve an accurate and concise forgery feature representation that counters the interference of task-unrelated features. Extensive experiments show the superior performance of SUMI-IFL to existing state-of-the-art methods, not only on in-dataset comparisons but also on cross-dataset comparisons. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Correlation theory

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