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DcDID: Highly privacy-secure decentralized identity system based on dynamic committee 24

DcDID: Highly privacy-secure decentralized identity system b...

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24th IEEE international conference on High Performance Computing and Communications, 8th IEEE international conference on Data science and systems, 20th IEEE international conference on Smart City and 8th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Wu, Xiaohua Feng, Xueqi Wu, Fengheng Wang, Jing University of Electronic Science and Technology of China Sichuan Chengdu China Chengdu Huanhaishaqiu Network Technology Co. Ltd Sichuan Chengdu China

ISBN: (纸本)9798350319934

the proposed self-sovereign identity satisfies the decentralized nature of blockchain. It ensures that users have complete control over their personal information. While decentralized identity systems have made great strides in guaranteeing credential uniqueness and securing user information, most existing systems are based on static committees. For decentralized identity systems on the blockchain, the committee nodes usually are made up of honest nodes on the chain. Nodes on the blockchain may join or quit at any time, so ignoring the dynamic changes of committee nodes can pose a severe threat to users' information security. In this paper, a decentralized identity system is proposed, based on dynamic committees(DcDID). the protocols in the system are constructed based on dynamic committee. A new contextual credential issuance protocol is constructed in the DcDId system. the protocol uses dynamic secret sharing techniques to store pairs of DIDs in the committee. this approach ensures the uniqueness of the credentials and dramatically improves the security of the user's private information during the dynamic change phase of the committee. Moreover, a new key recovery protocol is constructed in the DcDID system. In this protocol, asymmetric binary polynomial technique is used to change the secret sharing threshold. this approach ensures the security of the user's private key during the dynamic change phase of the committee. the security analysis included in this paper shows that DcDID significantly improves user privacy security compared to static committee-based systems. Our experimental results also show that our proposed protocol is feasible. © 2022 IEEE.

关键词： Blockchain

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Link Prediction for Opportunistic Networks Based on Hybrid Similarity Metrics and E-LSTM-D Models 24th

Link Prediction for Opportunistic Networks Based on Hybrid...

引用

24th international conference on Web Information systems Engineering, WISE 2023

作者： Yang, Xiaoying Li, Lijie Xu, Gang Song, Ming Zhang, Feng College of Computer Science Inner Mongolia University Hohhot010021 China Inner Mongolia A.R. Key Laboratory of Data Mining and Knowledge Engineering Inner Mongolia University Hohhot010021 China School of Computer and Information Technology Shanxi University Taiyuan030000 China

ISBN: (纸本)9789819972531

Link prediction is a crucial issue in opportunistic networks routing research. Static link prediction methods ignore the historical information of network evolution, which affects the prediction accuracy. In this paper, we propose a link prediction method (HS-LSTM) that combines hybrid similarity metrics and the E-LSTM-D model. the approach extracts structural features using hybrid similarity metrics, constructs a structural feature matrix, and applies the E-LSTM-D model to extract temporal features and predict the links that have not yet appeared in the network. Our experiments on three real datasets of opportunistic networks (Infocom5, MIT, and Haggle) shows that our proposed method outperforms the baseline method in terms of prediction accuracy. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Dynamic Continuous Distributed Constraint Optimization Problems 24th

Dynamic Continuous Distributed Constraint Optimization Probl...

引用

24th international conference on Principles and Practice of Multi-Agent systems (PRIMA)

作者： Hoang, Khoi D. Yeoh, William Washington Univ St Louis MO 63110 USA

ISBN: (纸本)9783031212024;9783031212031

the Distributed Constraint Optimization Problem (DCOP) formulation is a powerful tool to model multi-agent coordination problems that are distributed by nature. While DCOPs assume that variables are discrete and the environment does not change over time, agents often interact in a more dynamic and complex environment. To address these limiting assumptions, researchers have proposed Dynamic DCOPs (D-DCOPs) to model how DCOPs dynamically change over time and Continuous DCOPs (C-DCOPs) to model DCOPs with continuous variables and constraints in functional form. However, these models address each limiting assumption of DCOPs in isolation, and it remains a challenge to model problems that both have continuous variables and are in dynamic environment. therefore, in this paper, we propose Dynamic Continuous DCOPs (DC-DCOPs), a novel formulation that models both dynamic nature of the environment and continuous nature of the variables, which are inherent in many multi-agent problems. In addition, we introduce several greedy algorithms to solve DC-DCOPs and discuss their theoretical properties. Finally, we empirically evaluate the algorithms in random networks and in distributed sensor network application.

关键词： Multiagent systems Distributed constraint optimization problems Continuous DCOPs Dynamic DCOPs

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SMP-NoC: A Flexible and Efficient Shared Memory Protection Unit on Network-on-Chip 24th

SMP-NoC: A Flexible and Efficient Shared Memory Protection ...

引用

24th international conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wu, Teng He, Ying Wei, Shengjun Hu, Changzhen School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9789819615445

Network-on-Chip (NoC) is crucial for modern multicore systems, offering high throughput and low latency. However, its shared memory faces threats like illegal access and DDoS attacks. To enhance security, Memory Protection Units (MPUs) with permission tables are used to control access. NoC-MPU architecture uses TLBs and permission tables for request checks and domain isolation via CIDs, but this can cause high latency. To address this, DPU and NSM are combined for dynamic permission updates, though the tables remain static. Our paper introduces a novel Flexible and Efficient Real-Time Memory Protection Unit for NoC, featuring a hardware sandbox and taint-track monitor for pre-testing access requests. It supports dynamic memory region adjustments based on four permissions (RX, RWX, RW, R) and includes an access controller to counter DoS and side channel attacks. the design significantly boosts NoC security with minimal overheads: just 6.2% in throughput, 7.8% in area, and 4.8% in power, outperforming current solutions. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： hardware-level sandbox Network-on-Chip(NoC) shared Memory taint-track monitor

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Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicular Edge Computing 24th

Blockchain-Empowered Resource Allocation and Data Security ...

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24th international conference on Web Information systems Engineering, WISE 2023

作者： Wang, Maojie Han, Shaodong Chen, Guihong Yin, Jiao Cao, Jinli School of Cyber Security Guangdong Polytechnic Normal University Guangzhou510635 China Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia

ISBN: (纸本)9789819972531

Vehicular networking technology is advancing rapidly, and one promising area of research is blockchain-based vehicular edge computing to enhance resource allocation and data security. this paper aims to optimize resource allocation and data security in vehicular edge computing by leveraging blockchain technology, thereby improving the overall system efficiency and reliability. By integrating the computational, storage, and communication capabilities of vehicles with blockchain, efficient utilization of edge computing and fair resource allocation are achieved. Additionally, data encryption techniques are introduced to ensure data security and privacy protection. Experimental results demonstrate that the system can automatically identify and allocate the most suitable edge computing nodes, thereby enhancing the responsiveness and quality of computational tasks. the blockchain-based vehicular edge offloading system not only optimizes the performance of vehicular networking systems and enhances user experience but also strengthens data security and privacy protection, providing a novel solution for the development of the vehicular networking industry. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Influence of Temperature on the Frequency Characteristics of a Modal Filter based on a Microstrip Line with Two Side Grounded Conductors 24

Influence of Temperature on the Frequency Characteristics of...

引用

24th IEEE international conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Sagiyeva, Indira Y. Nurkhan, Bakhtiyar E. Salimkarri Tomsk State University of Control Systems and Radioelectronics Dept. of Television and Control Tomsk Russia

ISBN: (纸本)9798350336870

For the first time the paper presents the results of the study of temperature influence on the modal filter (MF) reflection| S11| and transmission| S21| coefficients magnitude frequency characteristics. the MF under consideration is based on a microstrip line with two side conductors grounded at both ends. the study is based on the results of simulations in the TALGAT system and measurements of the fabricated MF layout using the heat-cold chamber ESPEC-SU-262 and the vector network analyzer R&S ZV A40. the results of simulations and measurements at temperatures of -50, 25, and + 150°C for simulation and experiment, as well as for each temperature separately, are presented. A significant influence of temperature on| S11| and |S21| is shown. As the temperature increases, they decrease. the simulation and experimental results agree well at low frequencies and worse at high frequencies. this occurs due to the unaccounted frequency dependence of the parameters of SMA connectors and measuring cables. At the same time, the results at low frequencies showed the correctness of simulations in the TALGAT system. © 2023 IEEE.

关键词： Microstrip lines

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Multivariate Time Series Anomaly Detection Based on Graph Neural Network for Big Data Scheduling System 24th

Multivariate Time Series Anomaly Detection Based on Graph Ne...

引用

24th international conference on Web Information systems Engineering, WISE 2023

作者： Zhang, Shipeng Liu, Jing College of Computer Science Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9789819972531

With the increasing complexity of tasks in a big data task scheduling system, how to effectively organize the data collected from each subtask of a big data task scheduling system and model the spatiotemporal dependence between them, and then perform the accurate anomaly detection of multivariate time series is of great significance. Existing methods always could not effectively capture the relationship between different time series clearly, which leads to the inevitable false alarm. To address this issue, we propose a new multivariate time series anomaly detection framework called GraphTransformerAD, which combines GraphTransformer and LSTM. Specifically, each univariate time series is an independent feature, and graph neural networks are introduced to learn the complex dependence of multivariate time series in both time and feature dimensions. Runtime performance data are collected from the actual big data workflow task scheduling system, which is used to demonstrate the effectiveness of our proposed method. the proposed method outperforms baseline models on real datasets. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Anomaly detection

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Improving EEG-based Motor Execution Classification for Robot control 1

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14th international conference on Social Computing and Social Media (SCSM) Held as Part of the 24th international conference on Human-computer Interaction (HCII)

作者： Kanik, Sumeyra U. Demir Yin, Wenjie Ozgur, Arzu Guneysu Ghadirzadeh, Ali Bjorkman, Marten Kragic, Danica KTH Royal Inst Technol Div Robot Percept & Learning RPL Stockholm Sweden

ISBN: (数字)9783031050619

ISBN: (纸本)9783031050619;9783031050602

Brain computer Interface (BCI) systems have the potential to provide a communication tool using non-invasive signals which can be applied to various fields including neuro-rehabilitation and entertainment. Interpreting multi-class movement intentions in a real time setting to control external devices such as robotic arms remains to be one of the main challenges in the BCI field. We propose a learning framework to decode upper limb movement intentions before and during the movement execution (ME) with the inclusion of motor imagery (MI) trials. the design of the framework allows the system to evaluate the uncertainty of the classification output and respond accordingly. the EEG signals collected during MI and ME trials are fed into a hybrid architecture consisting of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) with limited pre-processing. Outcome of the proposed approach shows the potential to anticipate the intended movement direction before the onset of the movement, while waiting to reach a certainty level by potentially observing more EEG data from the beginning of the actual movement before sending control commands to the robot to avoid undesired outcomes. Presented results indicate that both the accuracy and the confidence level of the model improves with the introduction of MI trials right before the movement execution. Our results confirm the possibility of the proposed model to contribute to real-time and continuous decoding of movement directions for robotic applications.

关键词： BCI Deep learning Human-robot interaction

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Smart Contract Service Optimization in Blockchain-Cloud Collaborative Computing 24

Smart Contract Service Optimization in Blockchain-Cloud Coll...

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24th IEEE international conference on Mobile Data Management, MDM 2023

作者： Wan, Ji Hu, Kai Li, Jie Su, Hao Wu, Qingshun Li, Mingyuan Feng, Libo Pan, Yan Beihang University State Key Laboratory of Software Development Environment Beijing China Beihang Yunnan Innovation Institute Yunnan Key Laboratory of Blockchain Application Technology Kunming China Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China The First Affiliated Hospital of Zhengzhou University Zhengzhou China Yunnan University National Pilot School of Software Kunming China China Industrial Control Systems Cyber Emergency Response Team Institute of Software Beijing China

ISBN: (纸本)9798350341010

Smart contract is a trusted service provided on the blockchain, while cloud service is a traditional service mode with a large number of resources. the combination of the blockchain and cloud service is of great significance to the trusted expansion of services and the access to services inside and outside the blockchain. In this paper, we study the smart contract extension service in blockchain-cloud collaborative computing. the service module decoupling method of smart contract is proposed, and the parallel execution algorithm of smart contract service is designed, which improves the execution efficiency of smart contract service. Finally, this paper designs a secure data interaction method of smart contract and cloud service, which helps to maintain the data consistency between cloud computing and blockchain. the experimental results show that the proposed method can save at most 42.13% of the running time, and it can promote the data consistency between the cloud service and the blockchain. © 2023 IEEE.

关键词： Smart contract

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Representation of ICI as AWGN in PD-NOMA System Model 24

Representation of ICI as AWGN in PD-NOMA System Model

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24th IEEE international conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Kryukov, Yakov V. Pokamestov, Dmitriy A. Brovkin, Andrey A. Tomsk State University of Control Systems and Radioelectronics Dept. of Telecommunications and Basic Principles of Radio Engineering Tomsk Russia

ISBN: (纸本)9798350336870

Power Domain Non-Orthogonal Multiple Access (PD-NOMA) is recognized as one of the most promising technologies for next-generation multiple access in future wireless networks. Such multiplexing leads to the controlled inter-channel interference (ICI) cancelled at the receiver. In reality, ICI is represented as quadrature amplitude modulated (QAM) symbols (or other modulation). However, the vast majority of research papers use signal models in which ICI is represented as the additive white Gaussian noise (AWGN) with the equivalent power. Yet, such a replacement is not fully equivalent, because it reduces the accuracy of signal decoding. this is a significant simplification of the system model, which results in an additional inaccuracy in obtaining a number of system characteristics. this paper presents an approach that allows solving this problem and representing ICI as AWGN by means of a coefficient without increasing the decoding error. It also describes an expression for calculating the coefficient obtained and its performance confirmed by simulation results. © 2023 IEEE.

关键词： Decoding

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