检索结果-内蒙古大学图书馆

2nd International Conference on Network Simulation and Evaluation, NSE 2023

作者： An, Qi Zhu, Zifeng Li, Shudong Han, Weihong Wu, Xiaobo Li, Shumei Cyberspace Institute of Advanced Technology GuangzhouUniversity Guangzhou510006 China Department of New Networks Peng Cheng Laboratory Shenzhen518000 China School of Computer Science and Cyber Engineering Guangzhou University Guangzhou510006 China Computer College Jilin Normal University Siping136000 China

ISBN: (纸本)9789819745180

Faced with the growing threat of intranet attacks and numerous network security solutions, the defensive capabilities of network security solutions need to be evaluated in order to reasonably select a network security solution. However, the existing assessment of the defense capability of network security solutions mainly focuses on anti-DDoS devices, and lacks the assessment of the defense capability of the intranet, and it is complicated to obtain the values of assessment indicators during the assessment process. In addition, it is also difficult to obtain ideas for defense improvement of network security solutions. In the face of this situation, we propose an intranet defense capability assessment method for network security solutions based on the ATT&CK framework from an attack perspective. This method introduces the ATT&CK framework into the assessment of the intranet defense capability of network security solutions, constructs an indicator system with comprehensiveness and good scalability, and involves tactics, techniques and sub-technologies in the enterprise framework used by 138 APT organizations in the ATT&CK framework as objective data for indicator assignment, balancing the influence of attackers’ subjective experiences and preferences on the assessment results, and this method can easily obtain ideas to improve the intranet defense capability of network security solutions. The effectiveness of the proposed evaluation method is verified by conducting simulation experiments at a network range. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Intranets

来源：评论

学校读者我要写书评

暂无评论

NI-GDBA: Non-Intrusive Distributed Backdoor Attack Based on Adaptive Perturbation on Federated Graph Learning 25

NI-GDBA: Non-Intrusive Distributed Backdoor Attack Based on ...

引用

34th ACM Web Conference, WWW 2025

作者： Li, Ken Shi, Bin Wei, Jiazhe Dong, Bo School of Computer Science and Technology Xi’an Jiaotong University Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an China School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an China School of Distance Education Xi’an Jiaotong University Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an China

ISBN: (纸本)9798400712746

Federated Graph Learning (FedGL) is an emerging Federated Learning (FL) framework that learns the graph data from various clients to train better Graph Neural networks(GNNs) model. Owing to concerns regarding the security of such framework, numerous studies have attempted to execute backdoor attacks on FedGL, with a particular focus on distributed backdoor attacks. However, all existing methods posting distributed backdoor attack on FedGL only focus on injecting distributed backdoor triggers into the training data of each malicious client, which will cause model performance degradation on original task and is not always effective when confronted with robust federated learning defense algorithms, leading to low success rate of attack. What’s more, the backdoor signals introduced by the malicious clients may be smoothed out by other clean signals from the honest clients, which potentially undermining the performance of the attack. To address the above significant shortcomings, we propose a non-intrusive graph distributed backdoor attack(NI-GDBA) that does not require backdoor triggers to be injected in the training data. Our attack trains an adaptive perturbation trigger generator model for each malicious client to learn the natural backdoor from the GNN model downloading from the server with the malicious client’s local data. In contrast to traditional distributed backdoor attacks on FedGL via trigger injection in training data, our attack on different datasets such as Molecules and Bioinformatics have higher attack success rate, stronger persistence and stealth, and has no negative impact on the performance of the global GNN model. We also explore the robustness of NI-GDBA under different defense strategies, and based on our extensive experimental studies, we show that our attack method is robust to current federated learning defense methods, thus it is necessary to consider non-intrusive distributed backdoor attacks on FedGL as a novel threat that requires custom d

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Symbol Detection for Time-Varying Nonstationary Channels

引用

China Communications 2022年第3期19卷 158-171页

作者： Xuantao Lyu Wei Feng Ning Ge Xianbin Wang Research Center of Networks and Communications Peng Cheng LaboratoryShenzhen 518055China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering The University of Western OntarioLondonON N6A 5B9Canada

The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary *** this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol *** this end,we propose a symbol detector based on a long short-term memory(LSTM)neural *** the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better *** addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network ***,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube *** results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.

关键词： highly dynamic channel deep neural network long short-term memory basis expansion model symbol detection

来源：评论

学校读者我要写书评

暂无评论

Integrated Sensing,Computing and Communications Technologies in IoV and V2X

引用

China Communications 2023年第3期20卷 I0002-I0004页

作者： Shanzhi Chen FRichard Yu Weisong Shi Changle Li China Information and Communication Technology Group Co. Ltd.(CICT) State Key Laboratory of Wireless Mobile Communications SMIC IEEE VTS Mobile World newsletter IEEE Canadian Academy of Engineering(CAE) Engineering Institute of Canada(EIC) IET Department of Computer and Information Sciences at the University of Delaware(UD) State Key Laboratory of Integrated Services Networks of Xidian University

With the development of new generation of information and communication technology,the Internet of Vehicles(IoV)/Vehicle-to-Everything(V2X),which realizes the connection between vehicle and X(i.e.,vehicles,pedestrians,infrastructures,clouds,etc.),is playing an increasingly important role in improving traffic operation efficiency and driving safety as well as enhancing the intelligence level of social traffic services.

关键词： driving traffic operation

来源：评论

学校读者我要写书评

暂无评论

A Model Inference Attack Based on Random Sampling in DLaaS 24th

A Model Inference Attack Based on Random Sampling in DLaaS

引用

24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wu, Feng Sun, Shouyue Yang, Jiaxun Wu, Liwen Cui, Lei Qu, Youyang Yao, Shaowen Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Engineering Research Center of Cyberspace Yunnan University Kunming China School of Information Science and Engineering Yunnan University Kunming China Data61 Commonwealth Scientific and Industrial Research Organization BurwoodVIC3166 Australia

ISBN: (纸本)9789819615506

Deep learning as a service (DLaaS) has become an effective business solution in numerous domains. Nevertheless, its service form has been proven vulnerable to model inference by previous research. Existing work on model inference attack relies on strong assumptions, such as the attacker knows the sample variance and model structure, which may not thoroughly reflect the attack’s potential threats. In this paper, we propose MC-infer, a zero-knowledge, real-data-free, and black-box model inference method inspired by Monte-Carlo sampling. In particular, MC-infer feeds random noises obtained from different distributions to the target model, and sniffs the corresponding target distributions according to its feedback. Then many samples are taken in these distributions to obtain enough robust noises. Finally, the distribution represented by the target model is fitted through these noises to perform model inference. Our extensive evaluations demonstrate that MC-infer can effectively infer the target model with less information, and general noise perturbation on the model’s outputs cannot defend against MC-infer. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Active IRS Aided Secure Design for Integrated Sensing and SWIPT 10

Active IRS Aided Secure Design for Integrated Sensing and SW...

引用

10th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE 2024

作者： Xu, Jinlei Zhang, Jifa Liu, Mingqian Zhao, Nan Al-Dhahir, Naofal Wang, Xianbin School of Information and Communication Engineering Dalian University of Technology Dalian116024 China Xidian University State Key Laboratory of Integrated Service Networks Shanxi Xian710071 China Department of Electrical and Computer Engineering University of Texas at Dallas RichardsonTX75083 United States

ISBN: (纸本)9798331533922

In this paper, an active intelligent reflecting surface (IRS) assisted secure integrated sensing and simultaneous wireless information and power transfer system is proposed with the power splitting (PS) model adopted. Aiming to maximize the harvested power while satisfying the constraints of the integrated sidelobe level ratio and secrecy rate, an optimization problem is formulated to jointly determine the appropriate transmit beamforming, artificial noise (AN) vectors, PS ratios, as well as the amplification factors and phase shifts of the active IRS, which is non-convex and intractable. To overcome this challenge, we leverage semidefinite programming to transform it into a convex counterpart, and propose an alternating optimization algorithm to obtain a solution for the original problem. Simulation results demonstrate the effectiveness of the proposed scheme compared to benchmarks. © 2024 IEEE.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

引用

engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

来源：评论

学校读者我要写书评

暂无评论

A Shortest Path Query Approach for Encrypted Graphs Based on Padding Dictionary Structure

A Shortest Path Query Approach for Encrypted Graphs Based on...

引用

2023 China Automation Congress, CAC 2023

作者： Yang, Ming Zhang, Kaiyang Mu, Chao Wang, Xin Liu, Yuanlong Zhang, Heng Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center Ministry of Education Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China State Grid Shandong Electric Power Company Jinan China School of Computer Engineering Jiangsu Ocean University Lianyungang China

ISBN: (纸本)9798350303759

Hybrid intelligence has emerged as an innovative approach that synergistically combines the strengths of human intelligence and artificial intelligence (AI) to address complex problems. In this paradigm, knowledge graphs play a pivotal role by supplying vital background information and contextual understanding to hybrid intelligence systems. However, due to limitations in local storage capacity, managing large-scale graph data often requires outsourcing to cloud servers. Nevertheless, the use of untrusted cloud servers poses a risk of potential user data leaks. To address these concerns, this paper presents an encryption scheme specifically designed to protect graph data, enabling queries involving intermediate nodes in the shortest path between two nodes within the graph. The proposed scheme ensures the privacy and security of outsourced data by employing a novel method that utilizes padding dictionary structure encryption. This method ensures strict limitations on the cloud server's capabilities, restricting it solely to query operations, it effectively prevents any compromise of user data or unauthorized access to sensitive information, users can securely store and process their graph data on servers, significantly reducing the potential risk of data leakage and unauthorized breaches. To validate the feasibility and effectiveness of the proposed solution, practical experiments were conducted using real-world data. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

The Immense Impact of Reverse Edges on Large Hierarchical networks

引用

engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

来源：评论

学校读者我要写书评

暂无评论

PNRITR:Research on Positive and Negative Entity Region Perception Methods for Image-Text Retrieval 36

PNRITR:Research on Positive and Negative Entity Region Perce...

引用

36th International Conference on Software engineering and Knowledge engineering, SEKE 2024

作者： Zhang, Zhiping Sun, Tao Zheng, Hongyan Liu, Hao Liu, Gengchen Yang, Zhi Wang, Xiaoyu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)1891706594

The aim of cross-modal image-text retrieval is to heighten comprehension and to create robust associations between visual and textual content. This process entails a mutual querying and synchronization across various data formats. While conventional techniques have seen enhancements via attention-based approaches, they frequently miss the dynamics between corresponding and non-corresponding entity areas within image-text pairs. These techniques, often fixated on aligning image entities with textual terms, can overlook the congruence of entity characteristics, leading to less accurate localization. This research introduces PNRITR, an innovative strategy for cross-modal retrieval that leverages label learning to discern attributes absent from images, broadening the scope beyond just positive entity areas. PNRITR has delivered notable advancements on the Flickr30K and MS-COCO datasets. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：