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Adaptive Methods for Revenue Model Learning of a Slice Broker in the Presence of Adversaries

WIRELESS PERSONAL COMMUNICATIONS 2024年 1-19页

作者： Khan, Muhidul Islam Nencioni, Gianfranco Univ Stavanger Dept Elect Engn & Comp Sci Stavanger Norway

In the fifth-generation (5G) of mobile networks, Multi-Access Edge Computing (MEC) refers to the deployment of computing resources closer to the end-users for improved service delivery. In the context of 5G MEC, the slice broker plays a crucial role in managing the allocation of resources among the different network slices, which are logical networks on top of a shared infrastructure. The slice broker is a business entity that acts as an intermediary between the slice tenants and the infrastructure provider and is responsible for allocating resources (such as CPU, memory, and network bandwidth) required to set up the network. The slice broker must ensure that resources are allocated in a way that the revenue is maximized. In a dynamic environment, the slice broker must learn the revenue model adaptively and online. Adversaries can significantly reduce the revenue by misleading the system about the resources pretending to be selfish nodes, or creating noise. The slice broker should learn the revenue model in the presence of adversaries. We apply cooperative deep reinforcement learning with consensus mechanism and consensus deep learning to learn the revenue model adaptively. We also compare our proposed methods with the reference solution. Simulation results show that our proposed methods, especially the cooperative version, outperform the reference solution.

关键词： 5G MEC Slice broker Reinforcement learning consensus algorithm

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Distributed moving horizon fusion estimation for linear constrained uncertain systems

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ASIAN JOURNAL OF CONTROL 2024年第6期26卷 3027-3039页

作者： Wang, Shoudong Xue, Binqiang Qingdao Univ Coll Automat Qingdao 266071 Peoples R China

In this paper, the distributed moving horizon fusion estimation of uncertain systems with constraints of system noise and state variables is studied. Firstly, relying on the basic idea of consensus algorithm, the cost function in the performance index is reconstructed by weighted fusion of the state prediction values. Secondly, considering the performance index with uncertain parameters, the min-max optimization problem of the algorithm is transformed into the least squares optimization problem based on 2-norm regularization method. Thirdly, the scalar-weighted linear minimum variance fusion estimation strategy is used to realize the weighted fusion of local state estimation values. Then, on the premise of minimum network connectivity and collective observability, the stability of the proposed algorithm is studied, and the sufficient conditions for the expected convergence of the fused estimation error norm square are given. Finally, the effectiveness of the algorithm is verified by numerical simulation.

关键词： consensus algorithm moving horizon estimation performance index regularization method stability analysis uncertain parameters

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Distributed Secure Estimation Against Sparse False Data Injection Attacks

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年第5期54卷 2685-2697页

作者： Ma, Renjie Hu, Zhijian Xu, Lezhong Wu, Ligang Harbin Inst Technol State Key Lab Robot & Syst Harbin 150001 Peoples R China Harbin Inst Technol Chongqing Res Inst Chongqing 401200 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Nanyang 639798 Singapore Northeast Forestry Univ Coll Mech & Elect Engn Harbin 150040 Peoples R China Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China

Distributed cyber-physical systems (CPSs) are with complex and interconnected framework to receive, process, and transmit data. However, they may suffer from adversarial false data injection attacks due to the more open attribute of their cyber layers, and the connections with neighbor agents could aggravate the disastrous consequences on the system performance degradation. In this article, we focus on investigating distributed secure estimation paradigms against sparse actuator and sensor corruptions by virtue of combinational optimization. First, the consensus-based static batch optimization and secure observer design problems are established, based on which the concepts of sparsity repairability and restricted eigenvalues under attacks are discussed. Then, both the distributed projected heavy-ball estimator and distributed projected Luenberger-like observer are designed, in terms of the intensified combinational vote locations and distributed implementation of projection operator, with strict convergence guarantees. Finally, two numerical examples are performed to verify the effectiveness of our theoretical derivation.

关键词： Attack detection and identification consensus algorithm distributed cyber-physical system (CPS) distributed optimization secure estimation

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BLISS: blockchain-based integrated security system for internet of things (IoT) applications

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INTERNATIONAL JOURNAL OF INFORMATION SECURITY 2024年第3期23卷 1649-1665页

作者： Vishwakarma, Lokendra Das, Debasis Indian Inst Technol Jodhpur Dept Comp Sci & Engn VANET Lab NH 62 Karwar Rajasthan India

Cybersecurity is an essential part of IoT device functionality. Malicious acts cause the disclosure of private data, putting device performance at risk. As a result, creating efficient security solutions for authentication and confidentiality of both IoT devices and data exchange and integrity of data exchange networks has become a significant challenge. Furthermore, the traditional security mechanisms' high computation demands are not suitable for resource-constrained specific IoT devices. Therefore, we have proposed a security system for IoT applications using blockchain called BLISS, which ensures robust identification, authentication, confidentiality, and integrity of IoT devices and data exchange. Using smart contracts, the BLISS creates trustful clusters of IoT devices through an authentication process for data exchange. The BLISS is implemented on the Raspberry Pi 4 and the desktop PC, considering the Raspberry Pi 4 as an IoT device and the desktop as a cluster head. The performance analysis of the BLISS demonstrates the enhanced performance in the context of computation and energy consumption, which is 62-65% reduced. The storage and communication overhead is reduced by up to 70% compared with state-of-the-art schemes. The security analysis showed that the proposed scheme withstands many IoT-specific cyber threads.

关键词： Blockchain Internet-of-things (IoT) Security for IoT consensus algorithm

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Toeplitz Matrix Reconstruction algorithm for Rectangular Hollow Array

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2024年第1期2024卷

作者： Wei, Zihui Zhou, Jingyi Dai, Chenkai Wang, Lunsha Kong, Xiangjie Dong, Peng Hebei Univ Sci & Technol Planning Project Baoding Grant 2272P Baoding 071000 Peoples R China Hebei Univ Coll Qual & Tech Supervis Baoding 071000 Peoples R China

Among the directional angle calculation models of Bluetooth 5.1, the rectangular hollow array offers the advantage of shorter sampling time due to its fewer elements compared to traditional planar arrays. However, the antimultipath algorithms suitable for traditional planar arrays cannot be applied to rectangular hollow arrays. Therefore, this study proposes a virtual array filling algorithm, wherein four virtual matrices are inserted into the hollow matrix to transform the array into a uniform rectangular array. This algorithm ensures translation invariance of the rectangular array, enabling the application of the antimultipath coherent source algorithm to a rectangular hollow array. An algorithm for reconstructing Toeplitz matrices in two-dimensional uniform planar arrays is also proposed. Through the analysis of the spatial spectrum and angle estimation results of various algorithms, the effectiveness of the signal angle of arrival estimation theory is verified.

关键词： consensus algorithm

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Differential Privacy-Preserving consensus of Multi-Agent Systems under Replay Attacks 43

Differential Privacy-Preserving Consensus of Multi-Agent Sys...

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43rd Chinese Control Conference, CCC 2024

作者： Deng, Ying Dong, Huimin Mao, Bo Nanjing University of Finance and Economics College of Information Engineering Nanjing210023 China Shandong University School of Economics Shandong Jinan250100 China

ISBN: (纸本)9789887581581

This article explores the problem of differential privacy-protected consensus in discrete multi-agent systems (MASs) under replay attacks. To protect the differential privacy of the system, random noise is added to the interaction information among agents. Additionally, a pairing algorithm based on encryption is designed and introduced to more effectively detect and mitigate replay attacks in the communication network. Through these measures, the consensus of the MASs is achieved along with epsilon-differential privacy protection. Finally, an empirical demonstration through a numerical example validates the efficacy of the proposed strategy. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： consensus algorithm

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ON THE GEOMETRIC CONVERGENCE OF BYZANTINE-RESILIENT DISTRIBUTED OPTIMIZATION algorithmS

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SIAM JOURNAL ON OPTIMIZATION 2025年第1期35卷 210-239页

作者： Kuwaranancharoen, Kananart Sundaram, Shreyas Purdue Univ Elmore Family Sch Elect & Comp Engn W Lafayette IN 47907 USA

The problem of designing distributed optimization algorithms that are resilient to Byzantine adversaries has received significant attention. For the Byzantine-resilient distributed optimization problem, the goal is to (approximately) minimize the average of the local cost functions held by the regular (nonadversarial) agents in the network. In this paper, we provide a general algorithmic framework for Byzantine-resilient distributed optimization which includes some state-of-the-art algorithms as special cases. We analyze the convergence of algorithms within the framework, and derive a geometric rate of convergence of all regular agents to a ball around the optimal solution (whose size we characterize). Furthermore, we show that approximate consensus can be achieved geometrically fast under some minimal conditions. Our analysis provides insights into the relationship among the convergence region, distance between regular agents' values, step size, and properties of the agents' functions for Byzantine-resilient distributed optimization.

关键词： consensus algorithm convex optimization distributed algorithms distributed optimization fault tolerant systems linear convergence multiagent systems network security

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A novel lottery protocol based on quantum blockchain

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QUANTUM INFORMATION PROCESSING 2025年第2期24卷 1-24页

作者： Yang, Yu-Guang Qiu, Shi Wang, Yue-Chao Xu, Guang-Bao Jiang, Dong-Huan Beijing Univ Technol Coll Comp Sci & Technol Beijing 100124 Peoples R China Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Coll Math & Syst Sci Qingdao 266590 Peoples R China

The lottery business is a form of gambling activity operated by authority agencies. Due to the substantial economic interests, its security and fairness become the core elements of industry development. To maintain the trust of participants and ensure fair competition, blockchain technology has been widely applied in the lottery field due to the characteristics of decentralization, transparency, and immutability. However, with the rapid advancement of quantum computing, the security of traditional blockchain technology is challenged largely. To tackle this issue, a novel consensus mechanism which can resist quantum attacks is first proposed, based on a self-tallying quantum voting protocol. Then, a quantum circuit is designed, which can encode n-bit binary information into the relative phase of a quantum state and entangle the blocks by means of controlled-Z (CZ) gate, forming a quantum blockchain structure with timestamps. Finally, utilizing the designed quantum blockchain, a new type of lottery protocol is constructed. The proposed protocol meets the requirements of decentralization, unforgeability, verifiability, and quantum attack resistance. Compared to existing lottery protocols, it can support an arbitrary number of players, and only one communication is required for the ticket purchase process of each player, making it suitable for most of lottery game scenarios.

关键词： consensus algorithm Quantum blockchain Quantum coding Lottery protocol

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Fast and simple (1+E)Δ-edge-coloring of dense graphs

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THEORETICAL COMPUTER SCIENCE 2025年 1034卷

作者： Dhawan, Abhishek Univ Illinois Dept Math Champaign IL 61820 USA

({ ( 1 )2}) Let E is an element of(0,1)and , Delta is an element of N be such that Delta=Omega maxlog E , E log1E . Given an -vertex -edge simple graph of maximum degree Delta, we present a randomized ( log3 Delta /E2)-time algorithm that computes a proper (1 + E)Delta-edge-coloring of with high probability. This improves upon the best known results for a wide range of the parameters E, , and Delta. Our approach combines a flagging strategy from earlier work of the author with a shifting procedure employed by Duan, He, and Zhang for dynamic edge-coloring. The resulting algorithm is simple to implement and may be of practical interest.

关键词： consensus algorithm

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A multi-center federated learning mechanism based on consortium blockchain for data secure sharing

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KNOWLEDGE-BASED SYSTEMS 2025年 310卷

作者： Wang, Bin Tian, Zhao Liu, Xinrui Xia, Yujie She, Wei Liu, Wei Zhengzhou Univ Sch Comp & Artificial Intelligence Zhengzhou 450000 Peoples R China Zhengzhou Univ Sch Cyber Sci & Engn Zhengzhou 450000 Peoples R China Henan Key Lab Network Cryptog Technol Zhengzhou 450000 Peoples R China Zhengzhou Key Lab Blockchain & Data Intelligence Zhengzhou 450000 Peoples R China SongShan Lab Zhengzhou 450000 Peoples R China Henan Childrens Hosp Zhengzhou 450018 Peoples R China

Currently, federated learning enables hospitals to collaborate on model training without disclosing patient privacy data. However, it still faces challenges such as single point of failure and communication inefficiency. For this reason, this study innovatively combines consortium blockchain and federated learning. A multicenter federated learning mechanism based on consortium blockchain (MCFLM-CB) is proposed to optimize the security and efficiency of data collaboration and sharing. Firstly, the MCFLM-CB model uses the multi-party co-management feature of the consortium blockchain to replace the central server of federated learning, so that the system performs the training of the federated learning model in multiple centers. It also achieves the elimination of the disadvantages that a single centralized server controls the data model. Secondly, we propose a Dynamic Grouping-based Practical Byzantine Fault Tolerant (DG-PBFT) consensus algorithm. The algorithm performs regrouping and center node selection based on node state changes. It improves the consensus algorithm in blockchain system adaptive ability. Finally, we propose a reputation value-based weighted federal average algorithm. By synthesizing multiple reputation attributes to evaluate the reputation of participants, it comprehensively reflects the node performance. The accuracy and reliability of reputation values are improved. To prove the effectiveness of the method, we validated it on 12 large-scale standardized biomedical image sets MedMNIST. The results show that the model achieves 93.2% accuracy and significantly improves the efficiency of the blockchain.

关键词： Consortium blockchain Privacy protection Federated learning consensus algorithm

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