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2nd International Conference on Computer engineering and Application, ICCEA 2021

作者： Zhiqiang, Lin Jianshan, Peng Yechuan, Bi Xiaowei, Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665426169

With the advent of the network era, network security has attracted more and more attention. As the key node in the network, network key devices play an important role in protecting the internal network and ensuring the network security. For the vulnerability of network key devices, security analysis has become an important concern of security personnel. Fuzzing is an automatic and effective vulnerability mining technology. In this paper, we propose the first coverage feedback fuzzy testing framework based on KVM PT technology for network key devices, aiming to solve the feasibility of applying fuzzy tools in network critical devices. At the same time, a fuzzy test agent technology based on firmware modification is proposed to help speed up the call of testcases. We evaluated the framework on Cisco ASA firewall, and trigger CVE-2018-0101, which proves the effectiveness of the framework. © 2021 IEEE.

关键词： Network security

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Zero WFuzzer: Target-Oriented Fuzzing for Web Interface of Embedded Devices 4

Zero WFuzzer: Target-Oriented Fuzzing for Web Interface of E...

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4th IEEE International Conference on Computer and Communication engineering Technology, CCET 2021

作者： Zheng, Yan Dong, Weiyu Cheng, Hui State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665438902

With the popularization of embedded devices, security issues continue to occur. The existing automated security testing methods for embedded devices are mainly carried out from two aspects: the Web interface of the device or the firmware binary file. This paper proposes a testing framework ZeroWFuzzer that combines the Web interface of embedded devices with firmware binary, which automatically generates test cases through the Web interface, and uses binary instrumentation to guide the fuzzing test. Experiments in embedded devices have found that ZeroWFuzzer has higher efficiency and quantity of triggering vulnerabilities than the protocol fuzzing tool Boofuzz and the Web security testing tool Xray. © 2021 IEEE.

关键词： Firmware

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An Ensemble Approach with Clustering-Based Under-sampling for Imbalanced Classification 2

An Ensemble Approach with Clustering-Based Under-sampling fo...

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2nd International Conference on Artificial Intelligence and Education, ICAIE 2021

作者： Ren, Huajuan Ren, Shuai Yan, Lin Wang, Ruimin Jing, Jing Shi, Jiaqi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665424929

Class imbalance widely occurs in many real-world applications, which affects the recognition of important class to a certain extent. Ensemble methods that combined resampling are effective to alleviate the class imbalance problems. This paper presents a new ensemble approach with clustering-based under-sampling, called CNBoost, for learning from imbalanced data. This algorithm is based on the combination of Centers NN and boosting procedure. Centers NN, as an under-sampling utilizing the nearest neighbors of cluster centers, is used to provide a new training subset in each iteration of boosting, which makes the base learner learn the overall data distribution in each iteration of boosting. We compared the performance of the proposed algorithm with 3 popular ensemble methods. Out of 10 datasets and 3 measurements, CNBoost performs equally well or better than the other 3 methods in 25/30 categories. In addition, we discussed the effect of the base learner used in boosting on the performance of these algorithms. The results show that CNBoost is a promising approach with high classification accuracy and stability for dealing with imbalanced datasets. © 2021 IEEE.

关键词： Iterative methods

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mathematical modeling of lunar soft landing - Take chang'e-3 as an example 4

Mathematical modeling of lunar soft landing - Take chang'e-3...

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4th IEEE International Conference on Automation, Electronics and Electrical engineering, AUTEEE 2021

作者： Yang, Benchao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665428392

In this paper, the three-dimensional sphere dynamic model of lunar precise soft landing of the probe is discussed. Taking the National College Students' mathematical modeling competition as the background and Chang'e 3 lunar landing as an example, the lunar center inertial coordinate system and orbital coordinate system are established respectively to better describe the positional relationship between the moon and aircraft and the dynamic changes of aircraft. The coordinates of the near lunar point and the far lunar point are obtained. Through the changes of altitude, speed, pitch angle, yaw angle, longitude and latitude during landing, the landing preparation orbit of Chang'e-3 is determined. Then we analyze the six stages of chang'e-3 landing process one by one, and discuss the results. © 2021 IEEE.

关键词： Students

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HDBFuzzer-Target-oriented Hybrid Directed Binary Fuzzer 21

HDBFuzzer-Target-oriented Hybrid Directed Binary Fuzzer

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Yu, Yingchao Qin, Xiaojun Gan, Shuitao State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781450389853

In this paper, we propose a target-oriented hybrid directed binary fuzzer (HDBFuzzer) to solve the vulnerability confirmation problem based on binary code similarity comparison. HDBFuzzer combines macro function level direction fuzzing and micro path-constraint directed solving. For some branches with simple or loose constraints, it still uses directed mutation of the directed fuzzing to penetrate while for some really hard-to-penetrate constraints, it resorts to guided concolic execution. At the same time, in order to improve the efficiency of constraint solving, we propose a constraint solving method based on "path abstraction", which approximates the solution space by the linear expression and generates effective input utilizing the highly-effective sampling method towards the linear space. Then, under the guidance by the directed greybox fuzzing, HDBFuzzer can generate input that can quickly reach the vulnerable code region and finally crash the program under the test to confirm the vulnerability hidden in the binary program. We evaluate HDBFuzzer against AFLGo-B and QSYM on LAVA-M dataset and ten real-world programs, and the results show that HDBFuzzer is superior to AFLGo-B and QSYM on the bug discovery, bug reproduction and target reaching capabilities.. © 2021 Association for computing Machinery. All rights reserved.

关键词： Software testing

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Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data

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Journal of Energy Chemistry 2024年第3期90卷 120-132,I0005页

作者： Ziyou Zhou Yonggang Liu Chengming Zhang Weixiang Shen Rui Xiong State Key Laboratory of Mechanical Transmission for Advanced Equipment&College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400000China Department of Vehicle Engineering School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Department of Electrical Engineering Harbin Institute of TechnologyHarbin 150000HeilongjiangChina School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia

Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion *** main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation *** addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging *** incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV *** analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional *** validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 *** this level of precision for OCV estimation requires only around 50 s collection of partial charging *** validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed *** cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV *** method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.

关键词： Lithium-ion battery Open-circuit voltage Health diagnosis Deep learning

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TCLD-Net: A Transfer Learning Internet Encrypted Traffic Classification Scheme Based on Convolution Neural Network and Long Short-Term Memory Network

TCLD-Net: A Transfer Learning Internet Encrypted Traffic Cla...

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2021 IEEE International Conference on Communications, computing, Cybersecurity and Informatics, CCCI 2021

作者： Hu, Xinyi Gu, Chunxiang Chen, Yihang Wei, Fushan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665432085

The Internet is about to enter the era of full encryption. Traditional traffic classification methods only work well in non-encrypted environments. How to identify the specific types of network encrypted traffic in an encrypted environment without decryption is one of the foundations for maintaining cyberspace security. Traffic classification based on machine learning relies heavily on the prior knowledge of experts to construct feature sets. Although traffic classification based on deep learning can reduce human intervention, it requires a large amount of labeled data for parameter determination. This paper proposes a tCLD-Net model that combines transfer learning and deep learning. It can be trained on a small amount of labeled data to distinguish network encrypted traffic with a high accuracy. It pre-trains a CLD-Net model in the source domain data set, and fixes the parameters of the convolutional neural network module in it, and trains and tests it in the target domain data set. In order to verify the effectiveness of the tCLD-Net model, we use the ISCX public data set to conduct experiments. The results show that our proposed model can complete 100 epoches training in 208 seconds when the training set only occupies 20% of the target domain. And achieve a classification accuracy rate about 86%. This is 4% higher than the model without pre-training, and the training time is only one third of the model without pre-training. © 2021 IEEE.

关键词： Cryptography

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Analysis of TLS Encrypted Communication Behavior Based on Bipartite Graph and Traffic Information Embedding 4

Analysis of TLS Encrypted Communication Behavior Based on Bi...

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4th IEEE International Conference on Computer and Communication engineering Technology, CCET 2021

作者： Yan, Lin Jiang, Liehui Wang, Ruimin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665438902

Currently, encrypted traffic using the TLS protocol is widely used, and there are a lot of malicious and unknown behaviors. It is an important goal in the research field to detect the traffic behavior of TLS and maintain network security and stability. This article is based on TLS encrypted traffic, taking the multi-session communication traffic between the client and the server as the object, and carrying out traffic analysis on the generated bipartite graph. Different from the existing works, this paper focuses on the multiple attributes of TLS traffic and transforms it into a bipartite graph with rich attributes, and breaks the bottleneck of single session traffic detection, avoiding simple graph mining mode analysis. The results of anomaly detection and application classification experiments based on real data sets show that similar client application objects and application behaviors show similar traffic characteristics. Finally, we discussed the importance of using the behavioral similarity of client response objects to identify and detect abnormal traffic in network applications. © 2021 IEEE.

关键词： Embeddings

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Research and Practice of Blending Teaching of Database System Integrating Ideological and Political Theories 3

Research and Practice of Blending Teaching of Database Syste...

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

作者： Yao, Jinyang Liu, Fudong Wang, Junchao Zhao, Bo Shan, Zheng Xu, Peng Engineering and Advanced Computing State Key Laboratory of Mathematical Zhengzhou China

ISBN: (纸本)9781728184739

For the problem of the monotonous teaching form of the database system course, we integrate ideology and politics theories into the teaching design of the database system, combined with the 'Ideological and Political Theories teaching in All Course' concepts. And we have absorbed the advantages of online teaching into the offline teaching, forming an efficient teaching program. The program enable teachers to impart knowledge of professional courses to students while also deepening students' understanding of the connotation of ideology and politics theories. © 2021 IEEE.

关键词： Blending

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Optimal scheme for dynamic adjustment of active mirror in FAST system 5

Optimal scheme for dynamic adjustment of active mirror in FA...

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5th International Conference on Computer Science and Artificial Intelligence, CSAI 2021

作者： Zhou, Hongchuan Liu, Jiaqi Song, Junyan Yang, Benchao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781450384155

This paper mainly studies the optimal scheme of dynamic adjustment of active mirror in FAST system by establishing mathematical model. According to the constraints such as distance variation range, a mathematical model describing the dynamic trajectory of the position and angle of the active mirror is established, and the correctness of the solution of the model is verified by simulation. The optimal surface model is selected from all the results. When the measured object is directly above the fast system, it is modeled based on the ideal parabola to ensure that the expansion constraints and threshold conditions of the actuator are met. Because the distribution of actuator and cable in the whole fast system is not a uniform sphere, the change of radial distance of cable can be considered as the expansion of actuator;In addition, the model is optimized from two aspects: adjusting the position of focus on the horizontal plane and changing the size of zoom alignment. From these two aspects, the parabolic focusing range satisfying the expansion range is obtained. Finally, the optimization strategy of dynamic adjustment of active mirror in fast system is given. © 2021 ACM.

关键词： Actuators

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