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4th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2021

作者： Zhu, DI Pang, Jianmin Zhou, Xin Han, Wenjie Zhengzhou University Zhengzhou450002 China Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781665406925

As the mainstream of smart contract research, most Ethereum smart contracts do not open their source code, and the bytecode of smart contracts has attracted the attention of researchers. Based on the similarity measurement of smart contract bytecode, a series of tasks such as vulnerability mining, contract upgrading and malicious contract detection can be carried out. This paper proposes a method to measure the similarity of smart contract bytecode. Firstly, the key opcode combination of smart contract is summarized. When traversing the CFG(control flow graph) constructed by decompilation of smart contract bytecode, the opcodes in the basic block are pattern matched, and the features between the basic blocks are extracted according to the in-out degree, so as to enhance the similarity measurement effect of contract semantics in vector space. The experimental results show that the proposed method is greatly improved compared with the baseline. © 2021 IEEE.

关键词： Smart contract

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Taking Myopic Best Response Against the Hedge Algorithm 42

Taking Myopic Best Response Against the Hedge Algorithm

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42nd Chinese Control Conference, CCC 2023

作者： Guo, Xinxiang Mu, Yifen School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Academy of Mathematics and Systems Science The State Key Laboratory of Scientific and Engineering Computing Chinese Academy of Sciences Beijing China Academy of Mathematics and Systems Science The Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789887581543

With the rapid development of artificial intelligence (AI), the game between the human and machine/AI becomes more and more common. The related theoretical analysis becomes significant and necessary, which however is still rare. This problem involves evolution analysis and optimal control of dynamic game systems driven by learning algorithms. In this paper, we consider a finitely repeated two-player zero-sum game. We study the dynamic evolution process of the game system, in which one player employs the Hedge algorithm and the other player takes the myopic best response. By the updating formula of the Hedge algorithm, we define a quantity called the state and construct the state Transition Triangle Graph (STTG). Then, we prove that the game system is periodic after o(T) stages. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Artificial intelligence

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Versatility of π-d Conjugated Coordination Nickel Metal-Organic Frameworks as Electrode Materials of Metal-Ion Batteries

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Energy Material Advances 2024年第1期5卷 120-132页

作者： Zaohong Zhang Kaihui Xu Jing Yang Zhuoyu Ji Yunchen Ge Zhicong Shi Yongwei Zhang Kai Zhang Chuan Wu Jia Hong Pan State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures School of ResourcesEnvironments and MaterialsGuangxi UniversityNanning 530004China Low Carbon Energy Process Intensification Research Institute and MOE Key Laboratory of Resources and Environmental Systems Optimization North China Electric Power UniversityBeijing 102206China Institute of High Performance Computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology Guilin University of Electronic TechnologyGuilin 541004China School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Environmental Science and Engineering School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

Metal-organic frameworks have emerged as promising electrode materials for metal-ion batteries due to their superior structural ***,they face challenges such as poor reversibility and easy degradation during electrochemical redox ***,we report the synthesis ofπ-d conjugated coordination polymers through NH_(3)-vapor-assisted self-polymerization of NiCl_(2)·6H_(2)O with 1,2,4,5-benzenetetramine tetrahydrochloride(namely,Ni-BTA).The synthesized Ni-BTA exhibits an open lattice structure that enhances the capacity for metal-ion diffusion,ensuring prolonged electrochemical cycling ***,electrochemical characterizations reveal that Ni-BTA functions as a bifunctional material,serving as both cathode and anode materials for lithium-ion batteries(LIBs).After 1,000 cycles at 1.0 A g^(−1),the cathode and anode show high discharge capacities of 199.7 and 338.4 mAh g^(−1),***,symmetrical all-organic batteries constructed with Ni-BTA exhibit a high specific capacity of 30.6 mAh g-1 and an ultrastable coulombic efficiency of approximately≈100%after 6,000 cycles at 1.0 A g^(−1).Furthermore,Ni-BTA exhibits versatility as a robust cathode for aluminum ion batteries(AIBs),delivering a discharge capacity of 18.7 mAh g^(−1) after 10,000 cycles at 1.0 A g^(−1).These findings highlight the potential of Ni-BTA as a versatile and durable electrode materials for both LIBs and AIBs.

关键词： d conjugation electrochemical stability open lattice stru metal ion batteries electrochemical redox processesherewe lithium ion batteries coordination polymers electrode materials

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HHL Analysis and Simulation Verification Based on Origin Quantum Platform 4

HHL Analysis and Simulation Verification Based on Origin Qua...

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2021 4th International Conference on Mechatronics and Computer Technology engineering, MCTE 2021

作者： Liu, Xiaonan Jing, Lina Han, Lin Gao, Jie State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Henan Supercomputing Center Zhengzhou University Zhengzhou450001 China

Solving large-scale linear equations is of great significance in many engineering fields, such as weather forecasting and bioengineering. The classical computer solves the linear equations, no matter adopting the elimination method or Kramer's rule, the time required for solving is in a polynomial relationship with the scale of the equation system. With the advent of the era of big data, the integration of transistors is getting higher and higher. When the size of transistors is close to the order of electron diameter, quantum tunneling will occur, and Moore's Law will not be followed. Therefore, the traditional computing model will not be able to meet the demand. In this paper, through an in-depth study of the classic HHL algorithm, a small-scale quantum circuit model is proposed to solve a 2×2 linear equations, and the circuit diagram and programming are used to simulate and verify on the Origin Quantum Platform. The fidelity under different parameter values reaches more than 90%. For the case where the matrix to be solved is a sparse matrix, the quantum algorithm has an exponential speed improvement over the best known classical algorithm. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Linear equations

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Image Electronic Evidence Screening Based on Improved SSD 6

Image Electronic Evidence Screening Based on Improved SSD

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6th IEEE International Conference on Intelligent computing and Signal Processing, ICSP 2021

作者： Liu, Yafei Jiang, Liehui Liu, Tieming Zhang, Youwei Zhengzhou University Zhongyuan Network Security Research Institute Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9780738143705

With the development of information technology, electronic evidence plays an increasingly important role in the judicial trial. In Judicial Forensics, it is difficult to extract effective electronic evidence accurately and quickly from a large number of electronic data. Traditional means generally take artificial identification to collect, which takes a long time and is not efficient. Using SSD target detection and recognition algorithm instead of traditional means can effectively reduce the time of screening evidence, but the basic SSD neural network is prone to miss detection for small targets. To solve the above problems, an improved SSD-based image electronic evidence screening method is proposed. This method optimizes the SSD neural network adaptively, introduces the attention mechanism module in the shallow convolution layer of the network to improve the representation ability of the feature map, and fuses the image features obtained from different convolution layers with multi-scale features to increase the shallow feature information. The experimental data are used to test the improved algorithm and analyze the experimental results. It is found that compared with the original SSD neural network algorithm, the detection mean average precision of the improved algorithm is increased by 4.7%, reaching 84.3%, which shows the feasibility and effectiveness of the improved algorithm. © 2021 IEEE.

关键词： Multilayer neural networks

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Lightweight DCT-Like Domain Forensics Model for Adversarial Example 19th

Lightweight DCT-Like Domain Forensics Model for Adversarial ...

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19th International Workshop on Digital Forensics and Watermarking, IWDW 2020

作者： Zhao, Junjie Wang, Jinwei Nanjing University of Information Science and Technology Jiangsu210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China

ISBN: (纸本)9783030694487

Since the emergence of adversarial examples brings great security threat to deep neural network which is widely used in various fields, their forensics become very important. In this paper, a lightweight model for the forensics of adversarial example based on DCT-like domain is proposed. The DCT-like layer realizes the block conversion of data from the spatial domain to the frequency domain. Together with the color space transformation layer and the residual layer, the DCT-like layer realizes the simulation of JPEG quantization error. The feature statistical layer is used to obtain the statistical feature values of the feature map output by the frequency-division convolution, and at the same time, it also contains learnable hyperparameters. The group BN strategy ensures the effectiveness of the DCT-like layer and the feature statistical layer and promotes the accuracy of forensics. Experiments show that the proposed model not only reaches the highest accuracy we know, but also it only needs to train for one epoch to get a high-performance. © 2021, Springer Nature Switzerland AG.

关键词： Deep neural networks

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Modelization and analysis of dynamic heterogeneous redundant system

Modelization and analysis of dynamic heterogeneous redundant...

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作者： Wang, Wei Li, Guangsong Gai, Keke Tang, Yazhe Yang, Benchao Si, Xueming State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou China School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Computer Science and Technology Xi'an Jiaotong University Xi'an China Shanghai Key Laboratory of Data Science Fudan University Shanghai China

With the development and popularization of Internet technology, network security has become the focus of attention. Vulnerabilities and back doors are regarded as two of the main reasons of network security problems. Dynamic heterogeneous redundant (DHR) architecture is a typical framework of cyberspace mimic defense. It can make use of untrusted hardware and software components to construct a high reliable and high security information system. In this article, a mathematical model is set up for the DHR architecture, and the system security is characterized by vulnerability consistency rate and success rate of system attack. The antiattack ability of the DHR system is analyzed using the mathematical model. © 2020 John Wiley & Sons, Ltd.

关键词： Network security

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A Binary Function Name Prediction Method Based on Variable Alignment and Translation Model 23

A Binary Function Name Prediction Method Based on Variable A...

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Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application

作者： Bing Xia Jiabin Yin Yunxiang Ge Ruinan Yang Key Laboratory of Mathematical Engineering and Advanced Computing ZhongYuan University of Technology China Henan Key Laboratory on Public Opinion Intelligent Analysis ZhongYuan University of Technology China ZhongYuan University of Technology China

ISBN: (纸本)9798400709449

Binary function naming is a code analysis task that generates functional descriptions of functions, and its results can be applied in the fields of malicious code analysis, vulnerability causation analysis, and algorithm governance. Aiming at the shortcomings of the pseudocode abstract syntax tree being difficult to extract and the binary function naming scheme having low accuracy rate, a binary function naming prediction model A2N based on variable alignment and sequence translation model is proposed. First, A2N extracts the function variable features of binary files from debugging information and performs variable alignment with the pseudocode obtained from decompiling; then, it obtains the hierarchical structure of the binary functions and designs the node extraction rules to generate an abstract syntax tree AST for each function; then, extract the paths between the leaf nodes of the AST and serialize the tree structure to represent it; finally, with the help of the neural network translation model, establish a mapping between the AST and the binary function names to realize the prediction function. The experimental results show that compared with Dire, Nero and XFL models, the F1 value of A2N is improved by 84%, 44% and 14% on file-level isolation experiments respectively, and the F1 value reaches 80.94% on function-level isolation experiments.

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Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

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Journal of Computer Science & Technology 2023年第4期38卷 773-792页

作者：田文洪徐敏贤周光耀吴逵须成忠 Rajkumar Buyya School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science University of VictoriaVictoriaBCV8W 3P6Canada State Key Laboratory of Internet of Things for Smart City University of MacaoMacao 999078China School of Computing and Information Systems University of MelbourneMelbourne 3010Australia

Load balancing is vital for the efficient and long-term operation of cloud data *** virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consoli***,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring ***,we provide a new approach,called Prepartition,for load *** partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM *** this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained *** with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_*** also extend Prepartition to online load *** results show that our proposed approach also outperforms state-of-the-art online algorithms.

关键词： cloud computing physical machine(PM) virtual machine(VM) reservation load balancing Prepartition

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Breaking Limitation of Convergence in Continuous Optimization: Predefined-Time Gradient Flows 63

Breaking Limitation of Convergence in Continuous Optimizatio...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Zhang, Renyongkang Guo, Ge Gao, Zhenyu Yu, Miao Zhang, Lu Wang, Zhengsong Han, Meng Yin, Yanyan Northeastern University College of Information Science and Engineering Shenyang110819 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao066004 China Curtin University School of Electrical Engineering Computing and Mathematical Sciences PerthWA6102 Australia

ISBN: (纸本)9798350316339

This paper investigates the continuous-time unconstrained optimization via dynamical gradient flow systems. For strongly convex objective functions, a gradient flow with predefined time convergence is proposed, which is suitable for relaxing the objective function to only satisfy the PolyakLojasiewicz (P-L) condition. A predefined-time convergent Newton's flow is designed for the minimization of strictly convex functions. The proposed result is extended for strongly convex objective functions with time-varying parameters. In our schemes, the upper bound of convergence time can be used as a prior choice without involving system initialization and complex parameter calculations. The convergence of algorithms is rigorously proved by using the Lyapunov method. Numerical simulation illustrates the effectiveness of the proposed methods. © 2024 IEEE.

关键词： Lyapunov methods

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