检索结果-内蒙古大学图书馆

Achieving Fair and Accountable Data Trading Scheme for Educational Multimedia Data Based on Blockchain 17th

Achieving Fair and Accountable Data Trading Scheme for Educa...

17th EAI International Conference on Quality, Reliability, security and Robustness in Heterogeneous networks, QShine 2021

作者： Li, Xianxian Peng, Jiahui Shi, Zhenkui Li, Chunpei College of Computer Science Guangxi Normal University Guilin China Guangxi Key Lab of Multi-source Information Mining Security Guilin China

ISBN: (纸本)9783030914233

Educational resources have a higher need for copyright protection to avoiding illegal redistribution. The transactions of educational multimedia data resources can effectively promote the development of educational informatization and solve the island situation of educational resources. In the process of traditional transactions for educational multimedia data, there is always a third parties, which may lead to dispute and distrust. And the copyright is not well protected. In this paper, we propose a fair and accountable trading scheme for educational multimedia data. The scheme is based on blockchain to achieve accountability and secure storage with IPFS. And we aim to construct a relatively strong copyright protection model through digital fingerprint and watermark technology. We implemented and evaluated the scheme in Ethereum. The results show that our scheme can achieve well copyright protection and preserve the users’ privacy. The overall overhead is reasonable. © 2021, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation

CoinSeg: Contrast Inter- and Intra- Class Representations fo...

引用

International Conference on computer Vision (ICCV)

作者： Zekang Zhang Guangyu Gao Jianbo Jiao Chi Harold Liu Yunchao Wei School of Computer Science Beijing Institute of Technology School of Computer Science University of Birmingham WEI Lab Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network

Class incremental semantic segmentation aims to strike a balance between the model’s stability and plasticity by maintaining old knowledge while adapting to new concepts. However, most state-of-the-art methods use the freeze strategy for stability, which compromises the model’s plasticity. In contrast, releasing parameter training for plasticity could lead to the best performance for all categories, but this requires discriminative feature representation. Therefore, we prioritize the model’s plasticity and propose the Contrast inter- and intra-class representations for Incremental Segmentation (CoinSeg), which pursues discriminative representations for flexible parameter tuning. Inspired by the Gaussian mixture model that samples from a mixture of Gaussian distributions, CoinSeg emphasizes intra-class diversity with multiple contrastive representation centroids. Specifically, we use mask proposals to identify regions with strong objectness that are likely to be diverse instances/centroids of a category. These mask proposals are then used for contrastive representations to reinforce intra-class diversity. Meanwhile, to avoid bias from intra-class diversity, we also apply category-level pseudo-labels to enhance category-level consistency and inter-category diversity. Additionally, CoinSeg ensures the model’s stability and alleviates forgetting through a specific flexible tuning strategy. We validate CoinSeg on Pascal VOC 2012 and ADE20K datasets with multiple incremental scenarios and achieve superior results compared to previous state-of-the-art methods, especially in more challenging and realistic long-term scenarios. Code is available at https://***/zkzhang98/CoinSeg.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vulnerable Smart Contract Function Locating Based on Multi-Relational Nested Graph Convolutional network

arXiv

引用

arXiv 2023年

作者： Liu, Haiyang Fan, Yuqi Feng, Lin Wei, Zhenchun School of Computer Science and Information Engineering Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of Technology Hefei230601 China Anhui Provincial Key Laboratory of Network and Information Security Anhui Normal Unviersity Wuhu241002 China

The immutable and trustable characteristics of blockchain enable smart contracts to be applied in various fields. Unfortunately, smart contracts are subject to various vulnerabilities, which are frequently exploited by attackers, causing financial damage to users. Therefore, it is extremely important to perform effective vulnerability detection and locating to ensure the security of smart contracts. Deep learning has shown great advantages in smart contract vulnerability detection due to its powerful end-to-end feature learning. The previous deep learning based approaches to smart contract vulnerability detection focus on identifying whether there are vulnerabilities in a smart contract. However, this kind of detection cannot achieve fine-grained vulnerability detection, i.e., locating which function in the smart contract is vulnerable. In this paper, we study the problem of vulnerable smart contract function locating. We construct a novel Multi-Relational Nested contract Graph (MRNG) to better characterize the rich syntactic and semantic information in the smart contract code, including the relationships between data and instructions. An MRNG represents a smart contract, where each node represents a function in the smart contract and each edge describes the calling relationship between the functions. In addition, we create a Multi-Relational Function Graph (MRFG) for each function, which characterizes the corresponding function code. That is, each function is characterized as an MRFG, which corresponds to a node in the MRNG. Each MRFG uses different types of edges to represent the different control and data relationships between nodes within a function. We also propose a Multi-Relational Nested Graph Convolutional network (MRN-GCN) to process the MRNG. MRN-GCN first extracts and aggregates features from each MRFG, using the edge-enhanced graph convolution network and self-attention mechanism. The extracted feature vector is then assigned to the corresponding node i

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Range-gated laser image compression and encryption scheme based on bidirectional diffusion

引用

Optoelectronics Letters 2021年第10期17卷 630-635页

作者： LI Jinqing SHENG Yaohui DI Xiaoqiang MU Yining School of Computer Science and Technology Changchun University of Science and TechnologyChangchun 130022China Jilin Province Key Laboratory of Network and Information Security Changchun 130022China Information Center of Changchun University of Science and Technology Changchun 130022China School of Science Changchun University of Science and TechnologyChangchun 130022China

The existing image encryption schemes are not suitable for the secure transmission of large amounts of data in range-gated laser imaging under high noise *** at this problem,a range-gated laser imaging image compression and encryption method based on bidirectional diffusion is *** image data collected from the range-gated laser imaging source is sparsely represented by the discrete wavelet *** chaotic system is used to scramble the sparse matrix,and then the measurement matrix is constructed by the quantum cellular neural network(QCNN)to compress the *** addition,the random sequence generated by QCNN hyperchaotic system is used to carry out"bidirectional diffusion"operation on the compression result,so as to realize the security encryption of image *** comparative analysis of the security encryption performance of different compression ratios shows that the histogram sample standard of the encrypted image can reach about 10,and the information entropy value is more than 7.99,which indicates that the encryption scheme effectively hides the plaintext information of the original *** the encrypted image is attacked by different degrees of noise,this method can still reconstruct the image through the effective decryption *** experimental results show that this method realizes the secure compression and encryption of gated-laser imaging image data,and effectively ensures the security of data while reducing the amount of channel transmission data.

关键词： image diffusion encryption

来源：评论

学校读者我要写书评

暂无评论

BEW-YOLO: An Improved Method for PCB Defect Detection Based on YOLOv7

BEW-YOLO: An Improved Method for PCB Defect Detection Based ...

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Zhiyao Li Aimin Li Yuechen Zhang Xiaotong Kong Wenqiang Li 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 Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

The PCB defect object size is small and the detection process is susceptible to background interference, usually have the problem of missed and false detection. In order to solve the above problems, an improved method based on YOLOv7 is proposed in this paper. Firstly, the bi-level routing attention (BRA) has been added to the header of the original YOLOv7 model to capture global dependencies and ensure the accuracy of small object detection and localization. Secondly, the explicit visual center (EVC) block is introduced before the fusion of mid-level features and high-level features to capture the global remote dependencies of top-level features, extract the features in local corner regions, achieve a comprehensive feature representation. Finally, the loss function is improved by changing the loss function of the original model to Wise-IoU, which allows our model to focus more on ordinary-quality anchor boxes and improve the performance of the detector while decreasing the competitiveness of anchor boxes for high-quality samples and reducing the influence of low-quality samples on the detection results. The experimental results show that the improved model improves 5% in AP and 1.9% in both AR and mAP over the original YOLOv7 model. Meanwhile, comparison experiments are conducted on the data-enhanced PCB dataset, which proves the superiority of our model over other state-of-the-art models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-Channel Hypergraph Convolution Group Recommendation with Member information Enhancement 25

Multi-Channel Hypergraph Convolution Group Recommendation wi...

引用

25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Tianhao Gao, Qian Fan, Jun Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Shandong Jinan250014 China Qilu University of Technology Shandong Academy of Sciences Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Shandong Jinan250353 China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Shandong Jinan250014 China China Telecom Digital Intelligence Techonology Co Ltd Shandong Jinan250101 China

ISBN: (纸本)9798350330014

Group recommendation involves comprehensively considering various aspects, including members and items, to predict the overall interests of a group and recommend suitable items through a recommendation system. With the rapid evolution of the Internet, online group activities have become increasingly prevalent, making group recommendation a highly discussed topic within the realm of recommendation systems. However, current research in group recommendation still confronts the following challenges. Firstly, a predominant portion of group recommendation research focuses solely on aggregating group-level information, neglecting the valuable contribution of higher-order member-level insights to group recommendation. Moreover, some aggregation strategies overly prioritize fairness, thereby disregarding common real-world patterns. Secondly, previous studies have primarily relied on aggregating individual member interests to establish group preferences, lacking a holistic consideration of group dynamics. To tackle these challenges, this study introduces an innovative approach by implementing multi-channel hypergraph convolution within the member perspective. This approach aims to effectively extract higher-order insights from members by utilizing a member information enhancement module. By establishing group interconnections based on similarity and employing an adaptive fusion network to amalgamate multiple viewpoints, a final representation is derived. Experimental results demonstrate that our proposed model surpasses baseline models by 3% to 4% in terms of hit rate and accuracy, validating the efficacy of our approach. © 2023 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

KA$^{2}$2SE: key-Aggregation Authorized Searchable Encryption Scheme for Data Sharing in Wireless Sensor networks

引用

IEEE Transactions on Services Computing 2024年第1期18卷 226-238页

作者： Haijiang Wang Jianting Ning Wei Wu Chao Lin Kai Zhang School of Information and Electronic Engineering Zhejiang University of Science and Technology Zhejiang China School of Cyber Science and Engineering Wuhan University Wuhan China Faculty of Data Science City University of Macau Macau China College of Education Sciences Hong Kong University of Science and Technology Guangzhou China Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fuzhou China Guangdong Key Laboratory of Blockchain Security Guangzhou University Guangzhou China College of Computer Science and Technology Shanghai University of Electric Power Shanghai China

As a promising technology, key-aggregation searchable encryption with constant computation overhead is especially suitable for sensor nodes with limited computation resources in wireless sensor networks. However, in most of the existing key-aggregation searchable encryption schemes, the authorized aggregation key is generated in a deterministic way. As a result, these schemes suffer from “ key Forge Attack ” and “ Trapdoor Forge Attack ” that we proposed and hence fail to support the security property as they claimed (which is an important goal to be achieved in key-aggregation searchable encryption schemes). To fix these flaws, in this paper, we identify the security challenges related to key-aggregation searchable encryption and propose a lightweight key-aggregation authorized searchable encryption scheme based on attribute-based encryption, called KA $^security$ SE. It enables a data owner to share encrypted data with an authorized query user by issuing only a single authorized aggregation key, and the authorized query user only needs to submit a single trapdoor to the cloud server to perform keyword search. We formulate the security definitions for KA $^security$ SE and prove its security. Finally, empirical evaluations demonstrate that KA $^security$ SE is computationally efficient in comparison with existing schemes.

关键词： Encryption Cryptography keyword search Wireless sensor networks Servers Privacy Cloud computing security Probabilistic logic Authorization

来源：评论

学校读者我要写书评

暂无评论

Time Slot Correlation-Based Caching Strategy for information-Centric Satellite networks 1

引用

11th EAI International Conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

作者： Xu, Rui Di, Xiaoqiang Chen, Jing Cao, Jinhui Luo, Hao Wang, Haowei Qi, Hui He, Xiongwen Lei, Wenping School of Computer Science and Technology Changchun University of Science and Technology Changchun130022 China School of Information Engineering Henan Institute of Science and Technology Xinxiang453003 China Jilin Province Key Laboratory of Network and Information Security Changchun University of Science and Technology Changchun130022 China Information Center Changchun University of Science and Technology 130022 Changchun China Beijing Institute of Spacecraft System Engineering Beijing100094 China Beijing Institute of Space Mechanic and Electricity Beijing100094 China

ISBN: (数字)9783031344978

ISBN: (纸本)9783031344961

With the successful manufacture of highly stable and high-performance satellite processors, caching on satellites has become possible. information Centric networking (ICN) is introduced to satellite networks to address the growing need for diverse data services. However, existing caching policies in ICN still suffer from the shortage of rational planning of cache locations and redundancy of cache contents. Consequently, the time slot correlation-based caching strategy for satellite networks (TSCCS) is proposed. Firstly, the index of time slot correlation is designed to quantify the neighboring time slots’ coupling relationship, and then the DSAM network model with time slot correlation is established. Secondly, the significance of satellite nodes is evaluated from the local and global perspectives respectively based on the eigenvector centrality algorithm to filter out the dynamic set of cache nodes. Finally, probabilistic caching is performed at the set of caching nodes with the goal of reducing cached content redundancy, considering content popularity and access delay. The simulated outcomes indicate that the TSCCS caching policy is superior to the comparison method in the areas of cache hit rate, request latency, and server load. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Satellites

来源：评论

学校读者我要写书评

暂无评论

TrUStAPIS: a trust requirements elicitation method for IoT

TrUStAPIS: a trust requirements elicitation method for IoT

引用

作者： Ferraris, Davide Fernandez-Gago, Carmen Network Information and Computer Security Lab University of Malaga Malaga29071 Spain

The internet of things (IoT) is an environment of interconnected entities, which are identifiable, usable and controllable via the Internet. Trust is useful for a system such as the IoT as the entities involved would like to know how the other entities they have to interact with are going to perform. When developing an IoT entity, it will be desirable to guarantee trust during its whole life cycle. Trust domain is strongly dependent on other domains such as security and privacy. To consider these domains as a whole and to elicit the right requirements since the first phases of the system development life cycle is a key point when developing an IoT entity. This paper presents a requirements elicitation method focusing on trust plus other domains such as security, privacy and usability that increase the trust level of the IoT entity developed. To help the developers to elicit the requirements, we propose a JavaScript notation object template containing all the key elements that must be taken into consideration. We emphasize on the importance of the concept of traceability. This property permits to connect all the elicited requirements guaranteeing more control on the whole requirements engineering process. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Towards HDR and HFR Video from Rolling-Mixed-Bit Spikings

Towards HDR and HFR Video from Rolling-Mixed-Bit Spikings

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yakun Chang Yeliduosi Xiaokaiti Yujia Liu Bin Fan Zhaojun Huang Tiejun Huang Boxin Shi Institute of Information Science School of Computer Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University National Engineering Research Center of Visual Technology School of Computer Science Peking University National Key Lab of General AI School of Intelligence Science and Technology Peking University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

The spiking cameras offer the benefits of high dynamic range (HDR), high temporal resolution, and low data redundancy. However, reconstructing HDR videos in high-speed conditions using single-bit spikings presents challenges due to the limited bit depth. Increasing the bit depth of the spikings is advantageous for boosting HDR performance, but the readout efficiency will be decreased, which is unfavorable for achieving a high frame rate (HFR) video. To address these challenges, we propose a readout mechanism to obtain rolling-mixed-bit (RMB) spikings, which involves inter-leaving multi-bit spikings within the single-bit spikings in a rolling manner, thereby combining the characteristics of high bit depth and efficient readout. Furthermore, we introduce RMB-Net for reconstructing HDR and HFR videos. RMB-Net comprises a cross-bit attention block for fusing mixed-bit spikings and a cross-time attention block for achieving temporal fusion. Extensive experiments conducted on synthetic and real-synthetic data demonstrate the superiority of our method. For instance, pure 3 -bit spikings result in 3 times of data volume, whereas our method achieves comparable performance with less than 2% increase in data volume.

关键词： computer vision Computational modeling Redundancy Cameras Boosting Data models Pattern recognition

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：