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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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Mechanistic investigation of highly bendable magnesium alloy sheet fabricated by short-process manufacturing

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Journal of Magnesium and Alloys 2024年第10期12卷 4289-4310页

作者： Shiwei Xu Peijie Xiao Xiaofan Wu John Holmes Frédéric Mompiou Zhenyu Xiao Chen Jin Tianjiao Li Kuaishe Wang Zhuoran Zeng College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan UniversityChangsha 410082China Suzhou Research Institute of Hunan University Suzhou 215131China College of Engineering Computing and CyberneticAustralian National UniversityACT 2601Australia CEMES-CNRS Universitéde Toulouse29 rue J.MarvigToulouse 31055France Qinghai Salt Lake Teli Magnesium Co. Ltd.Xining 810000China International Joint Laboratory for Light Alloys(Ministry of Education) College of Materials Science and EngineeringChongqing UniversityChongqing 400044China School of Metallurgical Engineering Xi’an University of Architecture&TechnologyXi’an 710055China College of Materials Science and Engineering Hunan UniversityChangsha 410082China

In this study,a commercial magnesium alloy AZ31(Mg-3Al-1Zn-0.3Mn)sheet through a short manufacturing process was found to be ductile and highly formable in *** possessing a strong basal texture,the short-processed sheet without any annealing can be bent at a small radius,only 0.2 times its thickness in the 90°bending ***,it could withstand direct deformation by repeated *** in-situ microstructural characterization reveals that extension twin bands with strain localization appear in the bending *** subsequent flattening,these twin bands underwent detwinning,reducing local strain concentrations and enabling further bending *** outstanding bend formability originated from the significant-type dislocation loops slipping on the prismatic crystal planes within dynamic-recrystallized *** grains underwent a uniform refinement to several microns in the short manufacturing process and exhibited low residual *** active prismatic dislocation slip within refined grains was due to its much lower relative activation stress to basal slip(CRSSprism/CRSSbasal of only∼1.6)owing to the effective grain boundary ***,the prismatic dislocation activity was further enhanced when bypassing Al-Mn nano-particles during motion,leaving debris and loops that facilitated easy multiplication.

关键词： Magnesium Deformation Texture In-situ characterization Dislocation slip.

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Adversarial Example Attacks Against Intelligent Malware Detection: A Survey

Adversarial Example Attacks Against Intelligent Malware Dete...

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International Conference on Applied Machine Learning (ICAML)

作者： Xuyan Qi Yonghe Tang Huanwei Wang Tieming Liu Jing Jing State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou China

With the advancement of information technology and the increasing prevalence of the internet, the number of malware has experienced an exponential, and the security threat to users' property and privacy is becoming more serious. With the great success of artificial intelligence especially deep learning technology in fields such as computer vision and speech processing, deep learning are gradually introduced into the field of malware detection, to process large amounts of malware more efficiently. However, in recent years, researchers have discovered that the deep learning model itself also has security risks. While malware detection based on deep learning brings convenience and technical progress, it also introduces some new threats, such as adversarial examples. This paper investigates adversarial example attacks against deep learning-based malware detectors. First, We reviewed research on malware detection techniques. Then we analyze the works related to adversarial example attacks against intelligent malware detectors. Finally, we discuss the challenges and prospects in future research.

关键词： Deep learning Computer vision Technological innovation Privacy Perturbation methods Detectors Predictive models

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A software upgrade security analysis method on network traffic classification using deep learning

A software upgrade security analysis method on network traff...

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2020 International Conference on Urban engineering and Management Science, ICUEMS 2020

作者： Zhang, Bing State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

ISBN: (纸本)9781728188324

Nowadays, the vulnerability in the software upgrade process are extremely harmful to network security. However, the detection of upgrade vulnerability is facing serious difficulties and problems. Aiming at the current software upgrade vulnerability analysis problem, we propose a neural network model for traffic classification based on two levels of data packets and network flows. This method does not need to manually extract features and can learn the dependency relationship between data packets and networks well. It can make full use of comprehensive flow features for traffic classification. In order to evaluate the model, we built a dataset of software upgrade vulnerabilities and conducted relevant experiments on the CICIDS 2017 dataset. The experimental results show that compared with other RNN models, our model has the best performance, reaching a precision of 99.86% and an F1 score of 99.44%. At the same time, based on the pre-trained model, we use the software upgrade vulnerability dataset to fine-tuning the model, with the F1 score reaching 99.78%. © 2020 IEEE.

关键词： Neural network models

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