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International Conference on Computer Supported Cooperative Work in Design

作者： Hao Zhang Xiangzhi Liu Xiaoming Wu Chunlin Zhao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Accurate detection of students' behaviors in class-rooms through video surveillance is crucial for improving teaching quality. This paper presents LAF -DETR, a novel algorithm designed to address challenges such as dense student interactions and multi-scale variations in complex classroom environments. Key contributions include a lightweight convolution module to enhance the extraction of multi-scale features, a feature fusion module to reduce background noise and improve multi-scale feature integration, and a downsampling module to capture compre-hensive information across various behavior scales. Experiments on three public datasets (SCB-Dataset3-S, CrowdHuman, Smart-Classroom-Student-Behavior) show that LAF-DETR outperforms the baseline model by 2.8%, 1.9%, and 2.1 % in Average Precision (AP), respectively, demonstrating its effectiveness in handling occlusion and multi-scale detection challenges.

关键词： Accuracy Federated learning Education Feature extraction Video surveillance Transformers Robustness Real-time systems Data mining Image enhancement

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A Modified CSO Based on Complementary Learning

A Modified CSO Based on Complementary Learning

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第34届中国控制与决策会议

作者： Wei Li Zhou Lei Lei Wang School of Computer Science and Engineering Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology

Competitive swarm optimization algorithm(CSO) is an effective optimization ***,the population is easy to converge to the local optimal area in dealing with complex *** improve the performance of the CSO algorithm,this paper proposes a modified CSO base on complementary learning(CSO-CL).First,an optional archive is introduced to provide valuable information of evolutionary ***,the complementary learning strategies are designed,which not only enhance the ability of the algorithm to jump out of the local optimum,but also ensure a better balance between the exploration and the ***,the linear population size reduction strategy is used to improve the convergence speed of the proposed *** comparing with three state-of-the-art metaheuristic algorithms on the CEC2014 benchmark functions,it is proved that the proposed algorithm is competitive and effective.

关键词： Competitive Swarm Optimizer Evolutionary Computation Optional Archive

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Research on Firmware Simulation of Windows Embedded Compact System

Research on Firmware Simulation of Windows Embedded Compact ...

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International Conference on Computer Supported Cooperative Work in Design

作者： Dawei Zhao Zhen Zhang Lei Zhang Lijuan Xu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Shandong Academy of Sciences Qilu University of Technology Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Firmware simulation of embedded devices is an important technology to support security testing of embedded devices. However, most of the current firmware emulation targets are bare-metal or Linux-based firmware. The number of embedded devices based on Windows Embedded Compact (Windows CE) as the operating system occupies a certain market size, and there are certain security risks. Firmware extraction and system state simulation of embedded devices based on Windows CE are difficult. In order to solve the problem that embedded devices based on Windows CE system need firmware simulation methods and better support the security testing of embedded devices using Windows CE system, We propose a firmware simulation method for Windows CE systems. Combining the development board framework supported by QEMU and the specific application of embedded devices to be simulated, we make a simulation image that can run in QEMU. We verify our method on two commercial PLCs, and the experimental results show that our method can simulate the system state of PLC firmware.

关键词： Federated learning Operating systems Industrial control Emulation security Microprogramming Testing

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Gat-Ti: Extracting Entities From Cyber Threat Intelligence Texts

Gat-Ti: Extracting Entities From Cyber Threat Intelligence T...

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Artificial Intelligence, networking and Information technology (AINIT), International Seminar on

作者： Dawei Zhao Wenhao Sun Yang Zhou Lijuan Xu Xin Li Xiaohui Han Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331522285

ISBN: (纸本)9798331522292

In Cyber Threat Intelligence (CTI) analysis, existing named entity recognition (NER) models often suffered a decline in performance due to their inability to adapt to the specialized terminology and complex contexts of the cybersecurity domain. To address these challenges, we introduced a novel NER model-GAT-TI-specifically optimized for CTI. By integrating a Graph Attention network (GAT) and a Hybrid Context Vector into the deep learning framework, GAT-TI significantly improved both recognition accuracy and threat entity extraction efficiency. The model utilized a pre-trained BERT model to capture semantic information and built a Dependency Parse Tree (DPT) to enhance its understanding of sentence structures, enabling more accurate entity identification. The GAT layer further refined the analysis by capturing complex dependencies among entities. Additionally, the Hybrid Context Vector merged global and local contextual features, strengthening the model's comprehension. In experiments, GAT-TI achieved an F1 score of 93.67, demonstrating its superior performance in extracting threat entities from CTI reports. In summary, GAT-TI effectively supports automated extraction and analysis of cybersecurity threat information.

关键词： Adaptation models Accuracy Terminology Named entity recognition Feature extraction Vectors Cyber threat intelligence Data mining Computer security Context modeling

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RDGFuzz: A directed greybox fuzzing optimization method based on Rich-Branch nodes 22

RDGFuzz: A directed greybox fuzzing optimization method base...

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Proceedings of the 2022 6th International Conference on Electronic Information technology and Computer Engineering

作者： Zejun Wu Li Lu Qiong Jia Zhihao Chen State Key Laboratory of Mathematical Engineering and advanced Computing China National Local Joint Engineering Laboratory of Network Space Security Technology China Beijing Institute of Computer Technology and Application China

ISBN: (纸本)9781450397148

Directed fuzzing technology is one of the key technologies to quickly reach a specific location of software, and to conduct targeted testing or bug recurrence. However, directed fuzzing technology has some problems, such as unreasonable seed energy allocation, low code coverage and incomplete testing. To solve the above problems, this paper proposes an optimization method of directed fuzzing based on Rich-Branch nodes. In this method, the concept of Rich-Branch nodes is defined and the algorithm of extracting Rich-Branch nodes is given. The optimization method collects the coverage information of the target program in the running process, calculates the weights of covered functions and nodes in real time by combining CG and CFG of the target program, and generates a list of Rich-Branch nodes. According to the weights of Rich-Branch nodes, the seed energy allocation algorithm of AFLGo is optimized and improved. Compared with AFLGo, this optimization method improves the average code coverage of each targeted point by 56.79%, and has the same target reaching ability as AFLGo.

关键词： Rich-Branch nodes Directed fuzzing Code coverage rate Vulnerability discovery

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Interactive Medical Image Segmentation in Various Imaging Modalities: Current Status and Challenges

Interactive Medical Image Segmentation in Various Imaging Mo...

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International Conference on Computer Supported Cooperative Work in Design

作者： Huijuan Hao Wenpeng Wang Yu Chen Qingyan Dingl Fengqi Hao Hu Zhang Jinqiang Bai Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Interactive medical image segmentation plays a crucial role in medical diagnosis, treatment planning, and in-terventional procedures. With the rapid advancement of artificial intelligence and deep learning technologies, this field has not only seen significant improvements in the accuracy and efficiency of segmenting anatomical structures and pathological areas from medical images, but it has also made substantial strides in the development of user-centric interactive tools. The introduction of the Segmentation Anything Model (SAM) represents a significant expansion of prompt-driven approaches within the domain of image segmentation, introducing a plethora of previously untapped functionalities. However, due to the substantial differences between natural and medical images, the generalization capabilities of interactive segmentation models across different imaging techniques remain limited, necessitating the ongoing development of targeted interactive segmentation models. In this work, we provide a comprehensive overview aimed at extending the efficacy of SAM to various medical imaging modalities, encompassing diverse image analyses and domains. Additionally, we explore potential research directions for SAM in different medical imaging fields. Despite these advancements, the accuracy and robustness of segmentation models still largely depend on high-quality annotated data, which is costly and time-consuming to acquire. These research efforts herald significant forthcoming advancements in interactive medical image segmen-tation technology, with the potential to greatly improve patient outcomes and streamline medical procedures, thereby driving further development and innovation in the healthcare industry.

关键词： Image segmentation Analytical models Technological innovation Accuracy Image analysis Zero shot learning Streaming media Data models Robustness Medical diagnostic imaging

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Multi-Level Privacy Preserving Scheme for Visual IoT Data Based on Compressive Sensing

Multi-Level Privacy Preserving Scheme for Visual IoT Data Ba...

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International Conference on Computer Supported Cooperative Work in Design

作者： Dawei Zhao Le Ju Fenghua Tong Fuqiang Yu Xin Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

With the rapid growth of IoT technology, Visual IoT (VIoT) plays a key role in areas like security surveillance and intelligent transportation, where large volumes of sensitive data are collected and transmitted. Many applications face limitations in computing and storage, such as challenges in managing traffic data. Recently, Compressed Sensing (CS) theory has been applied to improve data acquisition and processing efficiency. However, existing CS-based privacy methods focus mainly on protecting single privacy zones through key-based control and lack support for hierarchical protection across multiple sensitive regions. To address this, we propose a multi-level privacy-preserving scheme for VIoT data using CS, offering full, partial, and no access levels to meet varying security needs. We also implement watermarks to prevent key-sharing attacks among partially authorized users. Experimental results demonstrate that the scheme ensures data security while minimizing time and space overhead, making it suitable for resource-limited VIoT scenarios.

关键词： Privacy Visualization Data privacy Surveillance Transportation Watermarking Traffic control Protection Compressed sensing License plate recognition

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Signature Scheme Based on The SM2 Algorithm in Fabric

Signature Scheme Based on The SM2 Algorithm in Fabric

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2021 International Conference on networking and network Applications, NaNA 2021

作者： Zhang, Yaling Wang, Hongyun Wang, Yichuan Ji, Wenjiang Zhu, Lei Xi'an University of technology School of computer science and engineering Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of technology Xi'an China

ISBN: (纸本)9781665441582

Based on the analysis and research of the widely used Hyperledger Fabric alliance chain structure, this paper proposes a digital signature scheme based on the national cryptographic algorithm SM2 which can be applied to Hyperledger Fabric. Firstly, two elliptic curve public-key cryptography algorithms are analyzed, and the feasibility of the SM2 in Fabric system is studied. Secondly, the Fabric system using the SM2 algorithm is designed and implemented, and the generation process of the Fabric chain address using the SM2 algorithm is given. Finally, experimental verification of the availability and performance of the Fabric system after the replacement of national cryptography algorithms is carried out. The experimental results show that the SM2 interface of the new Fabric alliance chain has good usability, and the average latency is reduced by 51.8%, and the transaction throughput is increased by 33.1%. © 2021 IEEE.

关键词： Blockchain

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OpenViewer: Openness-Aware Multi-View Learning

arXiv

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arXiv 2024年

作者： Du, Shide Fang, Zihan Tan, Yanchao Wang, Changwei Wang, Shiping Guo, Wenzhong College of Computer and Data Science Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Jinan China

Multi-view learning methods leverage multiple data sources to enhance perception by mining correlations across views, typically relying on predefined categories. However, deploying these models in real-world scenarios presents two primary openness challenges. 1) Lack of Interpretability: The integration mechanisms of multi-view data in existing black-box models remain poorly explained;2) Insufficient Generalization: Most models are not adapted to multi-view scenarios involving unknown categories. To address these challenges, we propose OpenViewer, an openness-aware multi-view learning framework with theoretical support. This framework begins with a Pseudo-Unknown Sample Generation Mechanism to efficiently simulate open multi-view environments and previously adapt to potential unknown samples. Subsequently, we introduce an Expression-Enhanced Deep Unfolding network to intuitively promote interpretability by systematically constructing functional prior-mapping modules and effectively providing a more transparent integration mechanism for multi-view data. Additionally, we establish a Perception-Augmented Open-Set Training Regime to significantly enhance generalization by precisely boosting confidences for known categories and carefully suppressing inappropriate confidences for unknown ones. Experimental results demonstrate that OpenViewer effectively addresses openness challenges while ensuring recognition performance for both known and unknown samples. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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Research on the Design of Government Data Governance Evaluation System under the Perspective of Digital Government 9

Research on the Design of Government Data Governance Evaluat...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Xu, Zirui Sun, Jinyang Lu, Zhe Han, Delong Qilu University of Technology Shandong Academy of Sciences Information Research Institute Shandong Academy of Sciences Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd. Jinan China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

In the context of the digital era, government data governance is a key factor in promoting the modernization of government governance, but there is a lack of a complete set of evaluation index system to standardize the content and scope of government data governance. This paper adopts the policy tool theory to code and analyze the 12 policies from the three policy tool dimensions of supply layer, demand layer, and environment layer, and proposes three first-level evaluation indicators of basic environment, actual effectiveness, and safeguard mechanism, on the basis of which the evaluation content is selected in a focused manner based on the integration of policy documents related to data governance. Meanwhile, a comprehensive, scientific and objective evaluation system of government data governance is constructed by adopting assessment means combining subjectivity and objectivity, and quantitative and qualitative. The system is designed to assess and guide the data governance practices of the domestic government, point out the direction for government departments at all levels to carry out data governance, and play an important role in promoting the transparency and efficiency of data management. © 2024 IEEE.

关键词： data governance digital government government information indicator system policy tools

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