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4th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021

作者： Yu, Fei Wei, Qiang Geng, Yangyang Wang, Yunchao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781728185347

Industrial network boundary protection equipment faces threats from attackers when protecting the industrial control system network. The similarity and static characteristics caused by large-scale and long-term deployment determine that it could only defend against known attacks but could not deal with unknown APT threats, which leads to the breakthrough of one defense line is equivalent to the breakthrough of all defense lines and may bring challenges to industrial production safety. This paper proposes a mimic defense model of industrial isolation gateway based on endogenous security. With the dynamic scheduling mechanism to transform the attack surface, the gateway selects multiple heterogeneous filter executors to process the same packet simultaneously. By comparing the processing results of each executor, anomaly detection is carried out to realize the dynamic defense of the industrial isolation gateway. The experimental results show that the industrial isolation gateway based on mimic architecture can significantly increase the difficulty of backdoor utilization, such as paralysis, rule tampering, and information theft, and effectively defend the industrial control system from the threats caused by the backdoors and vulnerabilities of the isolation gateway while exerting the normal boundary protection function. © 2021 IEEE.

关键词： Anomaly detection

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IPv6 Landmark Mining Based on Domain Name Screening and IPv4-IPv6 Connection 21

IPv6 Landmark Mining Based on Domain Name Screening and IPv4...

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5th International Conference on Electronic Information Technology and Computer engineering, EITCE 2021

作者： Liu, Minghao Sun, Yuchen Liu, Chong Zu, Shuodi Zhang, Fan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (纸本)9781450384322

Existing IP landmark mining technologies mainly focus on IPv4, and less attention is paid to the association between IPv4 and IPv6. The current IPv6 network has fewer reliable landmarks with limited accuracy, while the IPv4 network already has a large number of reliable landmarks. If IPv4 landmarks can be used in IPv6 landmark mining, the accuracy and efficiency of IPv6 landmark acquisition will be improved. To this end, this paper proposes an IPv6 landmark mining method based on domain name screening and IPv4-IPv6 connection. This method first uses the domain names of government agencies, top universities, and top websites as seed domain names, and continuously obtains a large number of domain names through web crawlers;then performs DNS resolution on the obtained domain names to obtain their corresponding IPv4 address and IPv6 address;and finally evaluate and analyze whether the two addresses are located in the same location, and determine whether to use it as an IPv6 landmark. This method successfully associates the IPv4 geolocation with the IPv6 geolocation, and uses the IPv4 landmarks to obtain and evaluate the IPv6 landmarks. Experimental results show that this method can obtain city-level IPv6 network landmarks more efficiently, and it also has a certain ability in street-level landmark mining. © 2021 ACM.

关键词： Mining

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Anti-obfuscation Binary Code Clone Detection Based on Software Gene 7th

Anti-obfuscation Binary Code Clone Detection Based on Softwa...

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7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021

作者： Tang, Ke Liu, Fudong Shan, Zheng Zhang, Chunyan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9789811659393

Information technology facilitates people’s lives greatly, while it also brings many security issues, such as code plagiarism, software in-fringement, and malicious code. In order to solve the problems, reverse engineering is applied to analyze abundant binary code manually, which costs a lot of time. However, due to the maturity of different obfuscation techniques, the disassembly code generated from the same function differs greatly in the opcode and control flow graph through different obfuscation options. This paper propose a method inspired by natural language processing, to realize the semantic similarity matching of binary code in basic block granularity and function granularity. In the similarity matching task of binary code obtained by different obfuscation options of LLVM, the indicator reaches 99%, which is better than the existing technologies. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Genes

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Tuning 2D magnetism in Fe3+XGeTe2 films by element doping

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National Science Review 2022年第6期9卷 163-170页

作者： Shanshan Liu Zihan Li Ke Yang Enze Zhang Awadhesh Narayan Xiaoqian Zhang Jiayi Zhu Wenqing Liu Zhiming Liao Masaki Kudo Takaaki Toriyama Yunkun Yang Qiang Li Linfeng Ai Ce Huang Jiabao Sun Xiaojiao Guo Wenzhong Bao Qingsong Deng Yanhui Chen Lifeng Yin Jian Shen Xiaodong Han Syo Matsumura Jin Zou Yongbing Xu Xiaodong Xu Hua Wu Faxian Xiu State Key Laboratory of Surface Physics and Department of Physics Fudan University Institute for Nanoelectronic Devices and Quantum Computing Fudan University College of Science University of Shanghai for Science and Technology Laboratory for Computational Physical Sciences(MOE) Fudan University Solid State and Structural Chemistry Unit Indian Institute of Science School of Electronic Science and Engineering Nanjing University Department of Physics University of Washington Department of Electronic Engineering Royal Holloway University of London Materials Engineering The University of Queensland Beijing Key Laboratory of Microstructure and Property of Advanced Materials Institute of Microstructure and Property of Advanced Materials Beijing University of Technology The Ultramicroscopy Research Center Kyushu University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Collaborative Innovation Center of Advanced Microstructures Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Centre for Microscopy and Microanalysis The University of Queensland Shanghai Research Center for Quantum Sciences

Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.

关键词： 2D ferromagnetic material Fe3+XGeTe2 film element doping above room temperature TC tunability

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Multi Association Semantics-Based User Matching Algorithm Without Prior Knowledge

Multi Association Semantics-Based User Matching Algorithm Wi...

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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2021

作者： Jiang, Qiuyan Gong, Daofu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Science and Information Qingdao Agricultural University Qingdao266001 China

ISBN: (纸本)9789811669620

Cross-network user matching is one of the basic issues for realizing social network data integration. Existing research based on structure features provides a good matching method for nodes with high-degree, but ignores the matching of nodes with low values. This paper proposes an unsupervised cross-network user matching algorithm based on association semantics to solve the problem of cross-network user matching. It can effectively solve the low-degree user matching problem when the quality of the text type attributes of network users cannot be guaranteed. First, build a social network graph based on multiple types of user behaviors, and define different association semantics according to different behaviors;then, walk based on the association semantics to obtain user node sequences with association semantics, and then combine the network embedding model to learn the user feature vector representation is obtained;finally, the user similarity is measured based on the user vector similarity, and then cross-network user matching is realized. The highlights of this paper are two folds. (1) We treat the association as nodes. (2) Social network user graphs with association semantics can enrich structure feature;walks based on association semantics can obtain walks that are closer to natural language short sentences. The experimental results show that the proposed method can effectively match user with similar behavior characteristics without any prior knowledge, and can effectively achieve the matching of low-degree nodes in heterogeneous networks. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantics

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Directed Association-based User Identification Algorithm 2

Directed Association-based User Identification Algorithm

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2nd International Conference on Computer, Big Data and Artificial Intelligence, ICCBDAI 2021

作者： Jiang, Qiuyan Gong, Daofu Liu, Fenlin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Science and Information Qingdao Agricultural University Qingdao266001 China

This paper studies the social network with directed association semantics, and proposes an unsupervised user identification algorithm (DAUM-P). The algorithm construct a user associations graph based on multiple types of directed user behaviors, and define directed associations;then, walk based on directed associations to obtain a walking sequence, and then combine the network embedding model to learn user characteristics vector representation;finally, the identification result is given based on the representation vector distance. Finally, the experiments show that the user identification effect is better than that of the baseline method. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Semantics

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Malicious Traffic Detection Model Refactor Method Based on Adaptive Sample Generation 5

Malicious Traffic Detection Model Refactor Method Based on A...

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5th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2022

作者： Jiao, Liang Fei, Jinlong Zhao, Min State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Tianjin University of Science and Technology School of Electronic Information and Automation Tianjin China

ISBN: (纸本)9781665479677

As machine learning models are widely used in malicious traffic detection, model security has become an important research topic. Aiming at the problems that the model refactor attack methods need a large amount of prior knowledge of the target model, rely on a large amount of real data, and have a narrow scope of application, a model refactor method based on adaptive sample generation was proposed. By means of an adaptive sample generation algorithm based on graph retrieval, a small number of real samples are used to quickly generate generated samples uniformly distributed in the input domain. The boundary of the refactored model is corrected according to the decision of the target model, the refactored model is iteratively trained by combining the network traffic feature selection method and the model hyperparameter optimization method, and the model refactor attack is finally realized. The refactor attack experiment against five malicious traffic detection machine learning models shows that the refactor rate and accuracy of the refactored model increase gradually with the increase of iteration rounds, and the refactor rate is more than 90%, using only the target model output label. © 2022 IEEE.

关键词： Iterative methods

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Thermally Evaporated ZnSe for Efficient and Stable Regular/Inverted Perovskite Solar Cells by Enhanced Electron Extraction

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Energy & Environmental Materials 2023年第5期6卷 440-448页

作者： Xin Li Guibin Shen Xin Ren Ng Zhiyong Liu Yun Meng Yongwei Zhang Cheng Mu Zhi Gen Yu Fen Lin Solar Energy Research Institute of Singapore(SERIS) National University of SingaporeSingapore 117574Singapore Key Laboratory of Advanced Light Conversion Materials and Biophotonics Department of ChemistryRenmin University of ChinaBeijing 100872China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Shandong Provincial Engineering and Technical Center of Light Manipulation and Shandong Provincial Key Laboratory of Optics and Photonic Devices School of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of High Performance Computing A^(*)STARSingapore 138632Singapore

Electron transport layers(ETLs)are crucial for achieving efficient and stable planar perovskite solar cells(PSCs).Reports on versatile inorganic ETLs using a simple film fabrication method and applicability for both low-cost planar regular and inverted PSCs with excellent efficiencies(>22%)and high stability are very ***,we employ a novel inorganic ZnSe as ETL for both regular and inverted PSCs to improve the efficiency and stability using a simple thermal evaporation *** TiO_(2)-ZnSe-FAPbl_(3)heterojunction could be formed,resulting in an improved charge collection and a decreased carrier recombination further proved through theoretical *** optimized regular PSCs based on TiO_(2)/ZnSe have achieved 23.25%efficiency with negligible *** addition,the ZnSe ETL can also effectively replace the unstable bathocuproine(BCP)in inverted ***,the ZnSe-based inverted device realizes a champion efficiency of 22.54%.Moreover,the regular device comprising the TiO_(2)/ZnSe layers retains 92%of its initial PCE after 10:00 h under 1 Sun continuous illumination and the inverted device comprising the C_(60)/ZnSe layers maintains over 85%of its initial PCE at 85℃for 10:00 *** highlights one of the best results among universal ETLs in both regular and inverted perovskite photovoltaics.

关键词： high efficiency long-term stability planar regular/inverted perovskite solar cells thermal evaporation ZnSe electron transport layer

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Vulnerability Digging for Software-Defined Network Controller Using Event Flow Graph Analysis

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Security and Communication Networks 2022年第0期2022卷

作者： Wu, Zehui Zhang, Wenbin Wang, Yunchao Yan, Chenyu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Software-defined network (SDN) controllers, the core of SDN network architecture, need to deal with network events of the whole network, which has huge program state space and complex logic dependency, with security issues related. Vulnerabilities in the SDN controller can paralyze the whole network. Existing controller testing methods are difficult to dig into the hidden logic vulnerability for their ignorance of the complex events interactions among controllers, apps, and data plane inputs. Different from file processing software, network software is driven by events, and the event flow can more accurately and comprehensively reflect the execution process. In this work, we propose an SDN controller vulnerability digging method based on event flow graph analysis. The proposed method consists of three main steps: first, we execute the instrumented controller in a normal environment and generate event flow graphs and then extract their features as reference. Second, we generate and execute test cases using the fuzzing method and dig the newly built event flow graphs with potential vulnerabilities. Finally, we manually examine and validate the potential vulnerabilities. To accurately discover abnormal subgraphs, we utilize graph feature extraction and analysis technologies, such as graph mining and clustering, to distinguish the normal graph and abnormal graph. We implement our method on the Ryu controller and compare it with other SDN testing methods, such as BEADS and Delta. The evaluation indicates that our method uncovered three new vulnerabilities that other methods failed to find. © 2022 Zehui Wu et al.

关键词： Controllers

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Robust Watermarking Based on Multi-layer Watermark Feature Fusion

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IEEE Transactions on Multimedia 2025年

作者： Wu, Shaowu Lu, Wei Luo, Xiangyang Sun Yat-Sen University School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Guangzhou510006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450002 China

The purpose of robust image watermarking is to embed a watermark into a carrier image in an invisible form and extract the watermark successfully even under noise interference conditions to achieve copyright confirmation and traceability. Although watermarking methods based on deep learning can improve the robustness by adding a noise simulation layer, few theoretical analyses of the codec structure have been conducted. Theoretical explainability is the theoretical basis for developing a network architecture, which plays a guiding role in network development. On the basis of the interpretability of convolutional networks, this paper analyzes the mathematical process of embedding and extracting watermarks in codecs and proposes a novel watermarking framework based on multi-layer watermark feature fusion. Specifically, the encoder can be a convolutional network structure of arbitrary depth, whereas the decoder needs only to adopt its corresponding deconvolution structure. To improve the quality and robustness of the generated watermarked image, the watermark is associated with an arbitrary layer feature space in the decoder. In the decoder, the network quickly converges to each original encoding feature space through the deconvolution structure, thus decoupling the watermark features. Finally, the watermark is extracted via the automatic fusion of multi-layer watermark features. The experimental results show that the proposed method is suitable for few-shot learning, and its invisibility, robustness and generalization performance on multiple datasets are significantly better than those of other advanced methods. © 2025 IEEE.

关键词： Decoding

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