检索结果-内蒙古大学图书馆

Frontiers Technology of information and computer (ICFTIC), IEEE International Conference on

作者： Duanzhen Li Shujiang Xu Haochen He Hongrui Xue 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 PR China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan PR China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Cross-chain technology plays a critical role in the process of interconnecting blockchains. However, all attention has been focused on how to achieve efficient cross-chain interoperability protocols, thus neglecting the most important security issues in cross-chain data interaction. Frequent network attacks and data privacy leaks have sounded the alarm for the safety of cross-chain data transactions. How to solve the problem of data ownership tracking in cross-chain transactions has become the top priority. This paper designs a cross-chain transaction tracking protocol based on multi-dimensional digital watermark fingerprints, using robust watermark, fragile watermark, and user identity key to achieve multi-dimensional tracking and supervision of cross-chain data transactions. Finally, this paper analyzes the feasibility and efficiency of the proposed protocol through experiments.

关键词： Data privacy Protocols Watermarking Fingerprint recognition Blockchains Safety Discrete wavelet transforms Interoperability

来源：评论

学校读者我要写书评

暂无评论

LateBA: Latent Backdoor Attack on Deep Bug Search via Infrequent Execution Codes 15

LateBA: Latent Backdoor Attack on Deep Bug Search via Infreq...

引用

15th Asia-Pacific Symposium on Internetware, Internetware 2024

作者： Yi, Xiaoyu Li, Gaolei Huang, Wenkai Lin, Xi Li, Jianhua Liu, Yuchen The School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai Shanghai China The Department of Computer Science North Carolina State University Raleigh United States

ISBN: (纸本)9798400707056

Backdoor attacks can mislead deep bug search models by exploring model-sensitive assembly code, which can change alerts to benign results and cause buggy binaries to enter production environments. But assembly instructions have strict constraints and dependencies, and these additional model-sensitive assembly codes destroy semantics and syntax and are easily detected by dynamic analysis or context-based detection. To escape from the dynamic analysis-based detection, we propose a novel latent backdoor attack (LateBA) scheme based on the locality principle of program execution, which only poisons a few of infrequent execution codes, minimizing the effects on the original code logic. In LateBA, a progressive seed mutating strategy is designated to change the American Fuzzy Lop (AFL)-based path search tool to pay more attention to infrequent execution codes. With this strategy, the optimal range to positions in the whole program is determined. Subsequently, triggers are target model-sensitive assembly instructions, and try to minimize the variables that have been called in the context instructions in the trigger. Finally, we employ code semantic feature comparisons to select precise trigger injection positions within these ranges. The selection criteria of the trigger injection position is whether the corresponding code segments in this position have a data dependency relationship with other code segments. We evaluate the performance of LateBA over 7 deep bug search tasks. The results demonstrate the attack success rate of the proposed LateBA is considerable and competitive against the baselines. © 2024 Owner/Author.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Model Meets Federated Learning:A Hierarchical Hybrid Distributed Training Mechanism for Intelligent Intersection Large-Scale Model

引用

Big Data Mining and Analytics 2024年第4期7卷 1031-1049页

作者： Chang Liu Shaoyong Guo Fangfang Dang Xuesong Qiu Sujie Shao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Network Security Center State Grid Henan Electric Power Company Information Communication BranchZhengzhou 450052China

The large-scale model(LSM)can handle large-scale data and complex problems,effectively improving the intelligence level of urban ***,the traffic conditions at intersections are becoming increasingly complex,so the intelligent intersection LSMs(I2LSMs)also need to be continuously learned and *** traditional cloud-based training method incurs a significant amount of computational and storage overhead,and there is a risk of data *** combination of edge artificial intelligence and federated learning provides an efficient and highly privacy protected computing ***,we propose a hierarchical hybrid distributed training mechanism for ***,relying on the intelligent intersection system for cloud-network-terminal integration,we constructed an I2LSM hierarchical hybrid distributed training ***,we propose a hierarchical hybrid federated learning(H2Fed)algorithm that combines the advantages of centralized federated learning and decentralized federated ***,we propose an adaptive compressed sensing algorithm to reduce the communication ***,we analyze the convergence of the H2Fed *** results show that the H2Fed algorithm reduces the communication overhead by 21.6%while ensuring the accuracy of the model.

关键词： intelligent intersections large-scale models edge artificial intelligence(AI) federated learning compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Highway Gates Dynamic Adaptation network For Knowledge Graph Entity Alignment 21st

Highway Gates Dynamic Adaptation Network For Knowledge Graph...

引用

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Yusuf, Nursharbat Yilahun, Hankiz Imam, Seyyare Hamdulla, Askar School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Multilingual Information Technology Urumqi830017 China School of National Security Studies Xinjiang University Urumqi830017 China

ISBN: (纸本)9789819601240

The Entity alignment aims to align entities across different Knowledge Graphs and plays an important role in knowledge fusion tasks. In recent years, existing methods have typically used multiple aspects of information to enhance the accuracy of matching, which makes the matching process more comprehensive. However, existing methods that integrate multiple features have relied on fixed weighting strategies, making it challenging to adjust the relative importance of each feature. Therefore, this paper proposes an entity alignment framework(HGEA) based on highway gates dynamic adaptive network. Firstly, HGEA aggregates the structure, name, and node importance of entities. Among them, to fully utilize of the structural information of the Knowledge Graphs, we propose an entity and relation representation strategy based on a graph attention network. Then, we have a highway gates dynamic adaptation network, which combines the gating mechanism and multi-level self-attention to dynamically adjust the weight of each feature to adapt to the information flow of different entity features and optimize the entity alignment. Experiments on three real-world cross-lingual datasets demonstrate that our framework surpasses the current state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Docker-based security protection system for container applications

Docker-based security protection system for container applic...

引用

2023 International Conference on computer network security and Software Engineering, CNSSE 2023

作者： Wang, Chen Zhu, Sheng Li, Weiwei State Grid Smart Grid Research Institute co. Ltd. Nanjing210003 China State Grid Key Laboratory of Information & Network Security Nanjing210003 China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

At present, smart grid information platforms mostly use containers to realize the miniaturization deployment of power services. However, containers interact frequently with the outside world, their performance is fragile, and they are easy to be paralyzed and become the target of attacks, which seriously affects the safe operation of the information platform. Therefore, this paper proposes a Docker based security protection system for container applications, designs the system architecture and each sub module, and focuses on the key technologies of container information collection and exception detection. The security system can record the behavior of Docker containers, use artificial intelligence technology to conduct real-time analysis on the recorded data, find exceptions in advance, identify attacks, and deal with security threats according to the pre established rules and strategies, so as to provide a comprehensive guarantee for the safe operation of the smart grid information platform. © 2023 SPIE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Don’t Forget Pairing-Friendly Curves with Odd Prime Embedding Degrees

IACR Transactions on Cryptographic Hardware and Embedded Sys...

引用

IACR Transactions on Cryptographic Hardware and Embedded Systems 2023年第4期2023卷 393-419页

作者： Dai, Yu Zhang, Fangguo Zhao, Chang-An School of Mathematics Wuhan University Wuhan China School of Mathematics Sun Yat-sen University Guangzhou China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Information Security Guangzhou China

Pairing-friendly curves with odd prime embedding degrees at the 128bit security level, such as BW13-310 and BW19-286, sparked interest in the field of public-key cryptography as small sizes of the prime fields. However, compared to mainstream pairing-friendly curves at the same security level, i.e., BN446 and BLS12-446, the performance of pairing computations on BW13-310 and BW19-286 is usually considered inefficient. In this paper we investigate high performance software implementations of pairing computation on BW13-310 and corresponding building blocks used in pairing-based protocols, including hashing, group exponentiations and membership testings. Firstly, we propose efficient explicit formulas for pairing computation on this curve. Moreover, we also exploit the state-of-art techniques to implement hashing in G1 and G2, group exponentiations and membership testings. In particular, for exponentiations in G2 and GT, we present new optimizations to speed up computational efficiency. Our implementation results on a 64-bit processor show that the gap in the performance of pairing computation between BW13-310 and BN446 (resp. BLS12-446) is only up to 4.9% (resp. 26%). More importantly, compared to BN446 and BLS12-446, BW13-310 is about 109.1% − 227.3%, 100% − 192.6%, 24.5% − 108.5% and 68.2% − 145.5% faster in terms of hashing to G1, exponentiations in G1 and GT, and membership testing for GT, respectively. These results reveal that BW13-310 would be an interesting candidate in pairing-based cryptographic protocols. © 2023, Ruhr-University of Bochum. All rights reserved.

关键词： Public key cryptography

来源：评论

学校读者我要写书评

暂无评论

FPPNet: Fast Privacy-Preserving Neural network via Three-Party Arithmetic Secret Sharing 15th

FPPNet: Fast Privacy-Preserving Neural Network via Three-Pa...

引用

15th EAI International Conference on Mobile Multimedia Communications, MobiMedia 2022

作者： Bi, Renwan Xiong, Jinbo Li, Qi Liu, Ximeng Tian, Youliang Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fuzhou350117 China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China Key Laboratory of Cryptography of Zhejiang Province Hangzhou Normal University Hangzhou311121 China Key Laboratory of Information Security of Network Systems College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China

ISBN: (纸本)9783031239014

Jointing multi-source data for model training can improve the accuracy of neural network. To solve the raising privacy concerns caused by data sharing, data are generally encrypted and outsourced to a group of cloud servers for computing and processing. In this client-cloud architecture, we propose FPPNet, a fast and privacy-preserving neural network for secure inference on sensitive data. FPPNet is deployed in three cloud servers, who collaboratively execute privacy computing via three-party arithmetic secret sharing. We develop the secure conversion method between additive shares and multiplicative shares, and propose three secure protocols to calculate non-linear functions, such as comparison, exponent and division that are superior to prior three-party works. Some secure modules for running convolutional, ReLU, max-pooling and Sigmoid layers are designed to implement FPPNet. We theoretically analyze the security and complexity of the proposed protocols. With MNIST dataset and two types of neural networks, experimental results validate that our FPPNet is faster than the related works, and the accuracy is the same as that of plaintext neural network. © 2022, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Resource Allocation and Trajectories Design for UAV-Assisted Jamming Cognitive UAV networks

引用

China Communications 2022年第5期19卷 206-217页

作者： Zhenhui Tao Fuhui Zhou Yuhao Wang Xiaodong Liu Qihui Wu School of Information Engineering Nanchang UniversityNanchang 330031China College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210000China Shanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and TelecommunicationXi’an 710121China School of Electronic Information Wuhan UniversityWuhan 430072China

Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity *** UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdropped.A UAV jamming assisted scheme is proposed.A joint resource allocation and trajectories optimization problem is formulated in a UAV-assisted jamming cognitive UAV network subject to diverse power and trajectory *** alternative optimization algorithm is proposed to solve the challenging non-convex joint optimization *** simulation results demonstrate the superiority of our proposed scheme and many meaningful insights are obtained for the practical design of cognitive UAV networks.

关键词： cognitive radio unmanned aerial vehicles communications physical layer security cooperative jamming

来源：评论

学校读者我要写书评

暂无评论

Research on liquid crystal display technology based on regional dynamic dimming algorithm 9

Research on liquid crystal display technology based on regio...

引用

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

作者： Yu, Zhitao Sun, Peng Zhou, Mingle Liu, Qianlong Zhao, Shilong Hisense Video Technology Co. Ltd. Qing Dao China Hisense Visual Technology Co. Ltd. Qing Dao 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 Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350391367

In vehicle liquid crystal display (LCD) technology has attracted much attention for its wide range of applications in automotive infotainment systems. However, conventional LCD technologies have limitations in terms of energy consumption and display quality, especially in the context of the increasing demand for high contrast and low energy consumption. To address these challenges, this paper carries out a study of LCD technology based on an area dynamic dimming algorithm. The technology significantly improves the contrast ratio of LCDs and effectively reduces energy consumption by dividing the backlight module into multiple independently adjustable regions and dynamically adjusting the backlight brightness of each region according to the image content. The results show that the region dynamic dimming algorithm proposed in this paper can effectively adjust the brightness of the backlight according to the image content, achieving higher display contrast and lower energy consumption. © 2024 IEEE.

关键词： Liquid crystal displays

来源：评论

学校读者我要写书评

暂无评论

Document-Level Relation Extraction Model Based on Boundary Distance Loss and Long-Tail Relation Enhancement 21st

Document-Level Relation Extraction Model Based on Boundary D...

引用

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Liu, Xin Yilahun, Hankiz Imam, Seyyare Hamdulla, Askar School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Multilingual Information Technology Urumqi830017 China School of National Security Studies Xinjiang University Urumqi830017 China

ISBN: (纸本)9789819601189

In today’s data-driven era, deriving meaningful insights from documents poses a considerable challenge. The task of Document-level Relation Extraction (DocRE) seeks to discern relationships among multiple entities within documents, mirroring real-world scenarios and introducing more complexity than sentence-level relation extraction (SLRE). DocRE encounters issues such as numerous widely dispersed entities, an imbalance between positive and negative instances, and a long-tail distribution of relation types. We introduce a model for document-level relation extraction that utilizes boundary distance loss and long-tail relation enhancement to tackle these challenges. This approach adeptly captures intricate interactions among entities, enhancing multi-relation extraction performance. Our model achieved improvements of 3.22% and 3.15% in F1 and Ign-F1 scores on the RE-DocRED dataset, respectively. Moreover, it significantly surpasses recent strong baseline models on the JacRED dataset. The experimental results confirm the model’s effectiveness and generalizability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Boundary distance adaptive threshold loss Document-level relation extraction Long-tail relationship enhancement Multi-relation extraction

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：