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Proceedings of the 2019 7th International Conference on Information Technology: IoT and Smart City

作者： Peng Shan Qingbao Li Ping Zhang Yanyang Gu State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

With the rapid development of computer technology and the iteration of malware, numerous computer malware detection methods have been proposed, among which malware detection based on machine learning has become an important research direction. Opcode sequences are often used as an important feature of machine learning models for training and testing. However, opcode sequences extracted orderly from raw disassembly text may not adequately reflect the behavior of executables. In order to solve this problem, this paper proposes a new malware detection method based on the control flow of executables. This method analyzes the control flow of executables and extracts execution traces from by the unit of function. This paper uses the execution traces to represent the behavior of the executables and present the execution traces by opcode sequences. In order to improve the training efficiency and reduce the feature dimensionality, this paper propose an x86 intermediate code. Then we convert the opcode sequences into the corresponding intermediate code sequences and vectorize them using Vector Space Model (VSM) for training and testing. This paper implements Naïve Bayes Classifier, Support Vector Machines and Random Forest for classification. The experiment result shows that the Random Forest algorithm has the best performance, with an accuracy of 90.8% and the model establishment time is 22s. Compared with the traditional methods based on disassembly text, the accuracy is improved by 1.4%, compared with the methods using x86 opcode, the efficiency is increased by 62%.

关键词： Control Flow Analysis Machine Learning Intermediate Code Malware Detection

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High-Ni Low-Co High-Capacity Li-Rich Cathode Materials Via Adjusting Li2mno3 Content and Li/Ni Mixing Structures

SSRN

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SSRN 2023年

作者： Wu, Zhen Zou, Kunyang Dai, Xin Zhang, Yu-Han Zhang, Xudong Wang, Hao Hou, Zhufeng Ma, Lijing Liu, Yan Chen, Yuanzhen Guo, Shengwu Liu, Yongning State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong University Xi’an710049 China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of Sciences Qingdao266101 China Center for High Performance Computing Network Information Center Xi’an Jiaotong University Xi’an710049 China Hefei Advanced Computing Center Operation Management Corp Ltd Hefei230088 China State Key Laboratory of Structural Chemistry Fujian Institute of Research the Structure of Matter Chinese Academy of Sciences Fuzhou350002 China International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong University Xi’an710049 China

Li-rich layered oxides (LLOs) are considered as the promising cathode materials for next-generation high energy density lithium-ion batteries (LIBs). However, severe voltage fade and capacity decay hinder their commercial applications. Increasing the Ni content in LLOs effectively improves the stability and discharge voltage, but shows reduced capacities, typically © 2023, The Authors. All rights reserved.

关键词： Lithium compounds

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One-step implementation of Rydberg nonadiabatic noncyclic geometric quantum computation in decoherence-free subspaces

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Physical Review A 2022年第6期105卷 062602-062602页

作者： Li-Na Sun F.-Q. Guo Zheng Shan M. Feng L.-L. Yan Shi-Lei Su School of Physics and Microelectronics Key Laboratory of Materials Physics of Ministry of Education Zhengzhou University Zhengzhou 450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430071 China Department of Physics Zhejiang Normal University Jinhua 321004 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou 511458 China

Quantum gates constructed by geometric phase are naturally robust to control errors due to the global nature of the geometric evolution path. Therefore, how to cope with the inevitable decoherence errors is worthy of serious attention for geometric quantum computation. Different from conventional nonadiabatic geometric quantum computation (NGQC), which needs the same evolution time for any geometric rotation angle, we have proposed and experimentally demonstrated nonadiabatic noncyclic geometric quantum computation (NNGQC) without the requirement of the cyclic evolution condition, which thus reduces decoherence errors due to shortened evolution time [J. W. Zhang et al., Phys. Rev. Lett. 127, 030502 (2021)]. In addition, the use of decoherence-free subspaces (DFS) is another effective strategy to protect quantum gates from dephasing error and has been studied in nonadiabatic holonomic quantum computation [G. F. Xu et al., Phys. Rev. Lett. 109, 170501 (2012)]. Motivated by previous studies, we propose a one-step scheme to implement single-qubit NNGQC operation in DFS constructed by two Rydberg atoms, and then generalize the scheme to the two-logical-qubit case in one step. The numerical results show that our scheme is robust against decoherence in contrast to the NGQC counterparts. The present scheme combines the features of NNGQC and DFS and can further reduce the impact of decoherence on gate infidelity, which may provide an option for the realization of Rydberg-atom-based quantum computation in the future.

关键词： Geometric & topological phases Quantum gates Rydberg atoms & molecules

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Malware detection method based on control flow analysis 7

Malware detection method based on control flow analysis

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7th International Conference on Information Technology: IoT and Smart City, ICIT 2019

作者： Shan, Peng Li, Qingbao Zhang, Ping Gu, Yanyang State Key Laboratory Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

关键词： Malware

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Highly efficient oxygen evolution and stable water splitting by coupling NiFe LDH with metal phosphides

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Science China Materials 2021年第7期64卷 1662-1670页

作者： Chengye Song Yi Liu Yuchao Wang Shuaihao Tang Wenkui Li Qian Li Jian Zeng Lei Chen Hongcheng Peng Yongpeng Lei State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China School of Materials and Mechanical Engineering Jiangxi Key Laboratory of Surface EngineeringJiangxi Science and Technology Normal UniversityNanchang 330013China Hunan Provincial Key Laboratory of Chemical Power Sources College of Chemistry and Chemical EngineeringCentral South UniversityChangsha 410083China School of Material Science and Engineering Central South University of Forestry and TechnologyChangsha 410004China Energy Materials Computing Center Jiangxi University of Science and TechnologyNanchang 330013China State Key Laboratory of Advanced Chemical Power Sources Guizhou Meiling Power Sources Co.Ltd.Zunyi 563003China

It is a great challenge to develop highly active oxygen evolution reaction(OER)electrocatalysts with superior *** this study,a NiFe layered double hydroxidedecorated phosphide(NiFe LDH@CoP/NiP_(3))was constructed to display satisfactory OER activity and good stability for water splitting in alkaline *** an overpotential of 300 mV,NiFe LDH@CoP/NiP_(3) achieved a current density of 82 mA cm^(-2) for the OER,which was 9.1 and 2.3 times that of CoP/NiP_(3) and NiFe LDH,***,the reconstruction behavior,during which oxyhydroxides formed,was studied by a combination of X-ray photoelectron spectroscopy,Raman spectroscopy,and scanning electron microscopy.A synergistic effect between NiFe LDH and CoP/NiP_(3) was also observed for the hydrogen evolution ***,when NiFe LDH@CoP/NiP_(3) acted as both the cathode and anode for overall water splitting,a high current density of 100 mA cm^(-2) was maintained for more than 275 *** addition,under Xe light irradiation,a solar-to-hydrogen efficiency of 9.89% was achieved for solar-driven water *** work presents the coupling of different active compositions,and can provide a reference for designing bifunctional electrocatalysts.

关键词： bifunctional electrocatalysis oxygen evolution reaction phosphides layered double hydroxides water splitting

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Time-Domain Transfer Path Analysis Based on Gaussian Process Latent Force Model and Least Squares

SSRN

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SSRN 2024年

作者： Zhu, Yu He, Zhicheng Zhou, Enlin L. Li, Eric Chen, Y.J. Gao, H. State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha410082 China School of Computing Engineering & Digital Technologies Teesside University Middlesbrough United Kingdom Chinese Scholartree Ridge Laboratory China North Vehicle Research Institute Beijing100072 China Liuzhou Wuling New Energy Vehicle Co. Ltd. Guangxi Automobile Group Co. Ltd. Liuzhou545005 China

The appearance of Time-domain transfer path analysis (TPA) has provided an effective means for addressing the issues of noise, vibration, and harshness (NVH) in mechanical systems under transient conditions. However, two primary challenges exist with this approach. Firstly, computing the generalized inverse of the frequency response functions (FRFs) matrix from excitations to indicators is prone to numerical instabilities, leading to ill-conditioned problems. Secondly, the accuracy of time-domain information extracted from existing frequency-domain data is relatively low. These issues diminish the precision of classical time-domain TPA methods in time-domain loads identification and impulse response functions (IRFs) recognition, thereby affecting their accuracy. In this work, we propose a novel time-domain TPA method that integrates the gaussian process latent force model (GPLFM) with the least squares (LS). Initially, this method explores the GPLFM in fluid-structure interaction (FSI) system. Secondly, a genetic algorithm (GA) is utilized to determine optimal parameters of the indicators. Subsequently, the vibration IRFs are identified using the LS. Finally, the contribution of each path to the targets' vibration is calculated using linear convolution, while a Kalman filter without measurement updates predicts the noise contribution. Case studies have demonstrated that the proposed method achieved higher accuracy in time-domain loads identification under multiple loading conditions compared to traditional methods using deconvolution filters. Additionally, the accuracy of calculating the contributions surpasses that of traditional methods employing linear convolution. © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Empirical investigation of stochastic local search for maximum satisfiability

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Frontiers of Computer Science 2019年第1期13卷 86-98页

作者： Yi CHU Chuan LUO Shaowei CAI Haihang YOU State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

The maximum satisfiability (MAX-SAT)problem is an important NP-hard problem in theory,and has a broad range of applications in *** local search (SLS)is becoming an increasingly popular method for solving ***,a powerful SLS algorithm called CCLS shows efficiency on solving random and crafted MAX-SAT ***,the performance of CCLS on solving industrial MAX-SAT instances lags far *** this paper,we focus on experimentally analyzing the performance of SLS algorithms for solving industrial MAXSAT ***,we conduct experiments to analyze why CCLS performs poor on industrial *** we propose a new strategy called additive BMS (Best from Multiple Selections)to ease the serious *** integrating CCLS and additive BMS,we develop a new SLS algorithm for MAXSAT called CCABMS,and related experiments indicate the efficiency of ***,we experimentally analyze the effectiveness of initialization methods on SLS algorithms for MAX-SAT,and combine an effective initialization method with CCABMS,resulting in an enhanced *** results show that our enhanced algorithm performs better than its state-of-the-art SLS competitors on a large number of industrial MAX-SAT instances.

关键词： empirical investigation stochastic local search maximum satisfiability industrial instances additive BMS

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Active Defense Technology Based on Natural Software Diversity in Java Web Services 4

Active Defense Technology Based on Natural Software Diversit...

引用

2020 4th International Workshop on advanced Algorithms and Control engineering, IWAACE 2020

作者： Liu, Zhenwu Zhang, Zheng Liu, Hao Zhang, Gaofei Chen, Yuan State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengZhou HeNan450001 China PLA Strategic Support Force Information Engineering University ZhengZhou HeNan450001 China Jiangnan Institute of Computing Technology WuXi JiangSu214083 China

With the popular use of network application services and the growing number of users, web services have become the main target of hackers. Traditional single software has insufficient security protection against unknown threats and is prone to various vulnerabilities. In this paper, we adopt a new type of active defense strategy in java web services. At different application layers, we use existing components based on the natural software diversity to form different software stacks, and use dynamic scheduling mechanisms to change the attack surface at all times to obtain security protection. Our analysis shows that the flexibility of java web services using this defense strategy is enhanced, and the exploitability of its vulnerabilities is effectively reduced. © Published under licence by IOP Publishing Ltd.

关键词： Web services

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Graph Neural Network Enabled Fluid Antenna Systems: A Two-Stage Approach

arXiv

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arXiv 2025年

作者： He, Changpeng Lu, Yang Chen, Wei Ai, Bo Wong, Kai-Kit Niyato, Dusit State Key Laboratory of Advanced Rail Autonomous Operation China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom Yonsei Frontier Laboratory The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

An emerging fluid antenna system (FAS) brings a new dimension, i.e., the antenna positions, to deal with the deep fading, but simultaneously introduces challenges related to the transmit design. This paper proposes an "unsupervised learning to optimize" paradigm to optimize the FAS. Particularly, we formulate the sum-rate and energy efficiency (EE) maximization problems for a multiple-user multiple-input single-output (MU-MISO) FAS and solved by a two-stage graph neural network (GNN) where the first stage and the second stage are for the inference of antenna positions and beamforming vectors, respectively. The outputs of the two stages are jointly input into a unsupervised loss function to train the two-stage GNN. The numerical results demonstrates that the advantages of the FAS for performance improvement and the two-stage GNN for real-time and scalable optimization. Besides, the two stages can function separately. © 2025, CC BY.

关键词： Graph neural networks

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Graph Neural Network Enabled Fluid Antenna Systems: A Two-Stage Approach

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IEEE Transactions on Vehicular Technology 2025年

作者： He, Changpeng Lu, Yang Chen, Wei Ai, Bo Wong, Kai-Kit Niyato, Dusit State Key Laboratory of Advanced Rail Autonomous Operation China Beijing Jiaotong University School of Computer Science and Technology Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China University College London Department of Electronic and Electrical Engineering LondonWC1E 6BT United Kingdom Yonsei University Yonsei Frontier Laboratory School of Integrated Technology Seoul03722 Korea Republic of Nanyang Technological University College of Computing and Data Science 639798 Singapore

An emerging fluid antenna system (FAS) brings a new dimension, i.e., the antenna positions, to deal with the deep fading, but simultaneously introduces challenges related to the transmit design. This paper proposes an "unsupervised learning to optimize" paradigm to optimize the FAS. Particularly, we formulate the sum-rate and energy efficiency (EE) maximization problems for a multiple-user multiple-input single-output (MU-MISO) FAS and solved by a two-stage graph neural network (GNN) where the first stage and the second stage are for the inference of antenna positions and beamforming vectors, respectively. The outputs of the two stages are jointly input into an unsupervised loss function to train the two-stage GNN. The numerical results demonstrate that the advantages of the FAS for performance improvement and the two-stage GNN for real-time and scalable optimization. Besides, the two stages can function separately. © 1967-2012 IEEE.

关键词： Graph neural networks

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