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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Zhang, Hengwei Li, Zheming Liu, Hao Yang, Bo Li, Chenwei Wang, Jindong State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Current white-box attack to deep neural networks have achieved considerable success, but not for black-box attack. The main reason is poor transferability, as the adversarial examples are crafted with single deep neural networks model, and excessively depend on that model. To address that problem, we propose a rotation model enhancement algorithm to craft adversarial examples. We improve rotation method in model enhancement. This algorithm constructs a possibility model to randomly rotate original images, and generates multiple transformed images. Therefore, we craft adversarial examples with single model, and boost attack on multiple models, which demonstrate considerable transferability and success rate for black-box attack. The simulation indicates the algorithm boost black-box attack with a 89.2% success rate. © 2022 IEEE.

关键词： Deep neural networks

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Code Clone Detection Based on Code Semantic Enhancement Model

Code Clone Detection Based on Code Semantic Enhancement Mode...

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2023 International Conference on Intelligent Communication and Computer engineering, ICICCE 2023

作者： Chunyan, Zhang Ziang, Shen Chen, Liang State Key of Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Beijing University of Civil Engineering and Architecture Department of Electrical and Information Engineering Beijing China

ISBN: (纸本)9798350395617

Code clones are code fragments that are similar in composition or semantics of code statements, which can significantly improve software development efficiency and reduce costs by improving the quality of reusable code. However, existing code clone detection methods ignore the source code structure information and sequence information seriously. In this paper, we launched our research on the harder-to-break Type IV code clone detection, and propose a new method, namely Aug_Clone, to complete code clone detection task. Firstly, we utilize our published code semantic enhancement model to obtain the code semantic vector. Secondly, we perform code clone detection by calculating the similarity between these semantic vectors. At last, we evaluate our method on a large public data set, and experimental results show improvement over the state-of-the-art benchmarks, which demonstrates the effectiveness and efficiency of our method. © 2023 IEEE.

关键词： Semantics

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Misleading Image Classification with Multi-shearing and Random Padding 6

Misleading Image Classification with Multi-shearing and Rand...

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6th International Conference on Electronic Information Technology and Computer engineering, EITCE 2022

作者： Li, Chenwei Li, Zheming Yang, Bo Zhang, Hengwei State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (纸本)9781450397148

Neural networks are vulnerable when input data is applied with human-imperceptible perturbations, which is called adversarial examples. When used in image classification models, adversarial examples mislead neural netwoks to classify images with wrong labels, posing great threat to network security. White-box attack has achieved considerable success rate, for the model structure is already known. But black-box attack remains to be improved, so as to the transferability. We refer to the model augmentation method in network training process, and apply to generating adversarial examples to reduce overfitting. Consulting fundamental methods in adversarial examples, we propose a multi-cropping transformation method to alleviate overfitting and enhance transferability. Firstly, referring to data augmentation, we multi-crop original images in every iteration with random possibilities in adversarial exaples generating process. Secondly, the gradient of model loss function is calculated, and the perturbations are added to original images. Finally, we generate adversarial examples with iterative perturbations. The validation of our method is verified on single models and ensemble models, and the transferability is improved, compared to other fundamental methods. © 2022 Association for computing Machinery.

关键词： Shearing

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Traceability Method of Network Attack Based on Evolutionary Game

Traceability Method of Network Attack Based on Evolutionary ...

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Zhang, Hengwei Zhang, Xiaoning Sun, Pengyu Liu, Xiaohu Ma, Junqiang Zhang, Yuchen State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Cyberspace is vulnerable to continuous malicious attacks. Traceability of network attacks is an effective defense means to curb and counter network attacks. In this paper, the evolutionary game model is used to analyze the network attack and defense behavior. On the basis of the quantification of attack and defense benefits, the replication dynamic learning mechanism is used to describe the change process of the selection probability of attack and defense strategies, and finally the evolutionary stability strategies and their solution curves of both sides are obtained. On this basis, the attack behavior is analyzed, and the probability curve of attack strategy and the optimal attack strategy are obtained, so as to realize the effective traceability of attack behavior. © 2022 IEEE.

关键词： Network security

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A Cross-Platform Instant Messaging User Association Method Based on Supervised Learning 4th

A Cross-Platform Instant Messaging User Association Method B...

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4th International Conference on Big Data and Security, ICBDS 2022

作者： Zhou, Pei Luo, Xiangyang Du, Shaoyong Shi, Wenqi Guo, Jiashan School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

ISBN: (纸本)9789819932993

To solve the multi-platform user association problem of complex trajectory matching process and high time cost in cross-platform association positioning of instant messaging users, and at the same time make full use of the information in user trajectories, this paper proposes a supervised learning-based cross-platform instant messaging user association positioning method. The algorithm firstly places probes in the area where the target may appear to obtain user information;then gets user trajectories through the obtained user distance information and time information;selects user features through the classification algorithm of supervised learning, and designs a cross-platform instant messaging user association localization method based on supervised learning, so as to increase the association efficiency and accuracy of cross-platform instant messaging user association. The method conducts specific experiments for the most commonly used instant messaging tools in China, WeChat and Stranger users, and the results show that the method can achieve efficient and reliable association for these two types of instant messaging users. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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Solve the False-Positive Problem of the Mimic System Based on the Best Mimic Component Set

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China Communications 2022年第5期19卷 253-266页

作者： Yuwen Shao Zheng Zhang Xiaomei Wang Chuanxing Pan Jiangxing Wu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China China National Digital Switching System Engineering and Technological R&D Center Zhengzhou 450002China

At present,there is a problem of false positives caused by the too vast mimic scope in mimic transformation *** studies have focused on the“compensation”method to deal with this problem,which is expensive and cannot fundamentally solve *** paper provides new insights into coping with the ***,this study summarizes the false-positive problem in the mimic transformation,analyzes its possible harm and the root ***,three properties about the mimic scope are *** on the three properties and security quantification technology,the best mimic component set theory is put forward to solve the false-positive *** are two algorithms,the supplemental method and the subtraction *** best mimic component set obtained by these two algorithms can fundamentally solve the mimic system’s false-positive problem but reduce the cost of mimic *** make up for the lack of previous researches.

关键词： mimic scope the best mimic component set false-positive rate mimic transformation

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Social User Geolocation Method Based on POI Location Feature Enhancement in Context 1

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30th International Conference on Computational and Experimental engineering and Sciences, ICCES 2024

作者： Liu, Yu Qiao, Yaqiong Liu, Yimin Du, Shaoyong State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou China School of Information Engineering North China University of Water Resources and Electric Power Zhengzhou China

ISBN: (数字)9783031687754

ISBN: (纸本)9783031687747

The geolocation information in social media user generated text is one of the important bases for inferring users' location. The existing methods often rely on the mentioned Point of Interest (POI) and location Indicative word in user generated text as the inference basis, in consideration of the lack of consideration of semantic information and the inaccuracy or incompleteness of POI contribute to the inaccuracy of user geolocation based on text. To address these issues, this paper proposes Social User Geolocation Method based on POI Location Feature Enhancement in Context (UGLE). Firstly, the POI in user-generated text is removed by deep neural network. Then, through three geographical traits of POI: location orientation, word frequency and word length, the problem of ambiguous POI location orientation in user generated text is solved. Finally, by combining the semantic information of the words around POI, the user vector with enhanced location features is generated, which improves the geolocation accuracy of social users. On the Weibo dataset, the proposed Method is compared with four existing typical methods, PaQL, SeFG, MNB-PART, and MNB-LGR. The results show that the proposed method's accuracy in inferring province-level and city-level locations is 76.78% and 62.56%, respectively. These results are 6.81% and 6.66% higher than the existing best results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

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Cathodic electrolyte engineering toward durable Zn–Mn aqueous batteries

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National Science Review 2023年第12期10卷 42-44页

作者： Wanhai Zhou Hong Jin Fan Dongyuan Zhao Dongliang Chao Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials State Key Laboratory of Molecular Engineering of Polymers College of Chemistry and Materials Fudan University School of Physical and Mathematical Sciences Nanyang Technological University

Zn–Mn aqueous batteries (ZMABs)present potential for grid-scale energy storage with the benefits of low cost,high safety and eco-friendliness [1].Since 1866 (Leclanchéwet cell), we have witnessed the prosperity ...

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Path test data generation using adaptive simulated annealing particle swarm optimization

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Soft computing 2024年第17-18期28卷 9587-9607页

作者： Jiao, Chongyang Zhou, Qinglei State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou450001 China Henan Information Engineering School Zhengzhou Vocational College of Industrial Safety Zhengzhou450000 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China

Software testing is an effective means of ensuring software quality. The cost of software testing is the main component of the total cost of software development. The generation of test data is very important in testing, because the efficiency of testing depends on the test data used. A significant part of software testing automation is the test data generation. How to automatically generate test datasets is still an open problem. Search-based software testing (SBST) is a process of generating test data that employs meta-heuristic methods to resolve tough NP-hard problems. The test data generation problem belongs to NP-hard problems. This paper focuses on the automatic generation of test data for path coverage based on control flow criteria in structural testing. Some meta-heuristic algorithms have been used to search for software test data. To advance the efficiency and effectiveness of path test data generation, an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm is proposed. The probabilistic jumping property of simulated annealing (SA) algorithm is introduced into the particle swarm optimization (PSO) algorithm to make the particle accept bad solution at a certain probability during the searching process, and therefore boost the capacity of the proposed algorithm to bounce from the local optimum. The fitness function is constructed by the branch function superposition to properly guide the search process. In addition, to improve the convergence speed of the algorithm, an adaptive adjustment scheme based on inertial weight and an adjustment scheme based on learning factor are proposed as well. The experimental results show that the proposed method can effectually avoid premature convergence and effectively upgrades the efficiency of generating test data automatically. It is also competitive in solving other complicated optimization problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Natur

关键词： Software testing

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A Vulnerability Automation Exploitation Method Based on Symbolic Execution

A Vulnerability Automation Exploitation Method Based on Symb...

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2023 International Conference on Electronic Information engineering and Data Processing, EIEDP 2023

作者： Ge, Xueshuai Liu, Tieming Xie, Yaobin Zhang, Yuanyuan Cyberspace Security Department State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Information service room Unit 32738 China

ISBN: (纸本)9781510666160

With increasing number of software vulnerabilities, the quantity of attacks utilizing malicious samples is also on rise, leading to intensified adversarial competition. In particular, the application of automatic vulnerability mining techniques has resulted in a significant increase in the number of vulnerabilities, but security researchers often do not have enough time to deal with them. This paper proposes a symbol-execution-based automated vulnerability exploitation method, which can achieve automation of vulnerability detection, classification and exploitation. Finally, this paper designs and implements a prototype system for symbol-execution-based automated vulnerability exploitation, and verifies its effectiveness through experiments. This research provides security analysts with an in-depth understanding of the types of vulnerabilities and determines methods for vulnerability exploitability, further improving the efficiency of analyzing and fixing vulnerabilities. © 2023 SPIE.

关键词： Automation

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