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52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

作者： Buchman, Ethan Guerraoui, Rachid Komatovic, Jovan Milosevic, Zarko Seredinschi, Dragos-Adrian Widder, Josef Informal Syst Toronto ON Canada Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (数字)9781665402606

ISBN: (纸本)9781665402606

Tendermint is a deterministic consensus protocol and is one of the most mature implementations of its kind. This implementation is used as the core for building State Machine Replication (SMR) platforms with Byzantine fault-tolerant (BFT) guarantees. A noteworthy deployment of Tendermint has been in continuous operation since 2019 within a blockchain called Cosmos Hub. The Cosmos Hub supports the development of decentralized applications, and stands as one of the largest and most stable ongoing deployments of a BFT SMR platform. While successful in practice, the Tendermint consensus protocol has no definitive description in the literature. It is not clear what makes this protocol unique or how it fits into a blockchain protocol stack. In this short paper, we revisit Tendermint. We contrast Tendermint with other major consensus algorithms, examining its unique design choices. We also focus on the requirements which dictated Tendermint's design. Lastly, we briefly analyze the accountability support which Tendermint provides.

关键词： Fault tolerance Fault tolerant systems Buildings consensus algorithm Decentralized applications consensus protocol

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Distributed K-Clustering with Exponential Convergence

Distributed K-Clustering with Exponential Convergence

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American Control Conference (ACC)

作者： Wang, L. Tron, R. Univ Calif Irvine Samueli Sch Engn Irvine CA 92697 USA Boston Univ Coll Engn Boston MA 02215 USA

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

We consider the problem of distributed K-clustering in a network of N agents where each agent holds a part of a dataset. The goal for the agents is to agree, in a distributed manner, on a set of K cluster centers that effectively summarize the entire dataset (e.g., by identifying points where the data is most concentrated), without explicitly exchanging all the data between all the agents or with a central node. First, we consider the special case when there is only one cluster (K = 1). We propose the Distributed 1-clustering Multiplier algorithm (Di 1MA), which ensures exponential convergence of all the copies of the cluster center at each agent to a common value by combining the properties of consensus algorithms and of the augmented Lagrangian method. Second, based on the previous case, we propose an algorithm called Distributed K-clustering Multiplier algorithm (DiKMA) to solve the case with K > 1 cluster centers. For this case, using ideas from switching algorithms, our solution alternates q steps of updates of the cluster centers with one update of the local assignments of data to cluster centers. We show that there must exist a q large enough such that the algorithm ensures the exponential convergence of the K cluster centers. We provide simulations to verify the proposed algorithms, and illustrate some of their properties.

关键词： Clustering algorithms Distributed databases Switches consensus algorithm Approximation algorithms Trajectory Distributed algorithms

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Optimal Selection of Intervention Timing in Opinion Dynamics

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IEEE Transactions on Automatic Control 2025年

作者： Zhang, Qi Wang, Lin Wang, Xiaofan Chen, Guanrong Shanghai Jiao Tong University Department of Automation Shanghai China Shanghai Jiao Tong University Department of Automation China Shanghai University School of Mechatronic Engineering and Automation China Shanghai Institute of Technology School of Electrical and Electronic Engineering Shanghai China City University of Hong Kong Department of Electrical Engineering Hong Kong Hong Kong

Differing from existing research on intervention strategies such as leader selection and edge addition, we investigate the impact of intervention timing in opinion dynamics. We employ the leader-based DeGroot model to formulate the evolution of opinions in social networks, wherein leaders represent organizations or parties that influence public opinion. We propose an optimal timing selection problem, in which a leader maximizes public opinion at a specific time by strategically selecting intervention times given a limited number of interventions. Our theoretical analysis shows that more interventions do not necessarily lead to better results, but additional interventions based on the existing intervention certainly do not worsen outcomes. Furthermore, we rigorously prove that intervention timing does not affect effectiveness if and only if all agents have the same weighted degree. Using the monotonicity and submodularity of the objective function, we develop a greedy algorithm and a time-importance-based heuristic algorithm to solve the problem. Our numerical simulations confirm the efficacy of these algorithms across both real-world social networks and synthetic random networks. © 1963-2012 IEEE.

关键词： consensus algorithm

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The Performance Evaluation of Blockchain-Based Security and Privacy Systems for the Internet of Things: A Tutorial

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IEEE INTERNET OF THINGS JOURNAL 2021年第24期8卷 17236-17260页

作者： Ferrag, Mohamed Amine Shu, Lei Guelma Univ Dept Comp Sci Gulema 24000 Algeria Nanjing Agr Univ NAU Lincoln Joint Res Ctr Intelligent Engn Nanjing 210031 Peoples R China Nanjing Agr Univ Coll Artificial Intelligence Nanjing 210031 Peoples R China Univ Lincoln Sch Engn Lincoln LN6 7TS England

This article presents research challenges and a tutorial on performance evaluation of blockchain-based security and privacy systems for the Internet of Things (IoT). We start by summarizing the existing surveys that deal with blockchain security for IoT networks. Then, we review the blockchain-based security and privacy systems for seventeen types of IoT applications, e.g., Industry 4.0, software-defined networking, edge computing, Internet of Drones, Internet of Cloud, Internet of Energy, Internet of Vehicles, etc. We also review various consensus algorithms and provide a comparison with respect to the nine properties, such as latency, throughput, computation, storage, and communication costs, scalability, attack model, advantage, disadvantage, etc. Moreover, we present the security analysis techniques and provide a classification into four categories, including Burrows, Abadi, and Needham (BAN) logic, game theory, theory analysis, and AVISPA tool. In addition, we analyze the performance metrics, blockchain testbeds, and cryptography libraries used in the performance evaluation of blockchain-based security and privacy systems for the IoT networks. Based on the current survey, we discuss the major steps to follow for building and evaluating blockchain-based security and privacy systems. Finally, we discuss and highlight open challenges and future research opportunities.

关键词： Security Internet of Things Blockchain Privacy consensus algorithm Performance evaluation Cryptography Blockchain experimentation environments Internet of Things (IoT) privacy security testbeds

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Proof of Pseudonym: Blockchain-Based Privacy Preserving Protocol for Intelligent Transport System

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IEEE ACCESS 2021年 9卷 163625-163639页

作者： Johar, S. Ahmad, N. Durrani, A. Ali, G. Univ Peshawar Dept Comp Sci Peshawar 25120 Khyber Pakhtunk Pakistan Prince Sultan Univ Coll Comp & Informat Sci Riyadh 12435 Saudi Arabia

Intelligent Transportation System is the future for safe and secure transportation. Vehicles in the ITS share basic safety information which can prompt the disclosure of the real identity of the vehicles. Thus, adversaries can misuse these safety messages. Pseudonyms are alias granted to vehicles by trusted authorities to conceal their original identities. To avoid linkability, various pseudonym generation and distribution protocols have been proposed. Such protocols pose overheads in the system as they are performed by Central Authorities. Therefore, re- utilizing the existing pseudonyms through shuffling is the most optimal mechanism for ITS. The Blockchain is a digital ledger and tamper-resistant record of transactions. It eliminates the need for central authority as well as provides anonymity of transactions resulting in more secure and privacy-protected solutions. To handle distribution optimization issues in the pseudonym shuffling process without a central authority, the blockchain is used with its distributed consensus. The shuffling results are logged in blocks as transactions. Pseudonym shuffle randomness is achieved via blockchain and it provides robustness in the structure. When one system fails, the rest would continue to work. The method also provides a fully traceable record in case of certification revocation. The existing blockchain-based pseudonym shuffling mechanism uses traditional consensus algorithms to support the cryptography operation. This leads to overhead in terms of execution time and memory usage. This research proposes Proof of Pseudonym consensus protocol for the shuffling scheme to improve the efficiency of consensus as compared to Proof of Work, Proof of Kernel Work and, Proof of Elapsed Time in terms of time and memory. The execution time of Proof of Pseudonym is shorter than other algorithms. The security and privacy analysis revealed that our scheme achieves identity privacy, unlinkability, and non-repudiation properties. Threat

关键词： Blockchains Privacy Peer-to-peer computing consensus algorithm Safety Servers Proof of Work Blockchain proof of work proof of kernel work proof of elapsed time proof of pseudonym

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Cooperative control of the DC-link voltage in VSC-MTDC grid via virtual synchronous generators

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FRONTIERS IN ENERGY RESEARCH 2024年 12卷

作者： Han, Huachun Li, Qun Li, Qiang State Grid Jiangsu Elect Power Co Ltd Elect Power Res Inst Nanjing Peoples R China

Introduction: Virtual Synchronous Generators (VSGs) are used in Voltage Source Converter-based Multi-Terminal High-Voltage Direct Current (VSC-MTDC) systems to enhance power system stability. However, the MTDC framework can lead to instability due to reduced inertia in certain grid areas, especially during load switching at VSC stations. This instability is exacerbated by untimely adjustments of the VSG's power setpoint, leading to voltage and frequency ***: This study introduces a cooperative control approach for the DC voltage of the VSG, employing a consensus algorithm and Model Predictive Control (MPC). This method aims to achieve incremental power for the VSG and provide interactive power commands for both the grid side and the wind farm side. The consensus algorithm ensures coherent system adjustments, while the MPC algorithm tracks DC-side voltage changes in real ***: The application of this cooperative control approach significantly enhances DC voltage regulation performance. It effectively reduces the extent of frequency drops and mitigates secondary frequency drop (SFD) issues, particularly those arising from the use of wind farms for frequency regulation and the associated speed recovery in wind turbine ***: The increase in supplemental power effectively utilizes the energy stored in DC-side capacitors for power balance regulation and introduces additional inertial power into the system. Electromagnetic transient simulations have confirmed the effectiveness of the consensus MPC-VSG method, demonstrating its ability to optimize the dynamic performance of VSC-MTDC systems and promote stability in DC voltage and ***: The findings suggest that employing the consensus MPC-VSG method offers a promising solution for enhancing the stability and operational efficiency of VSC-MTDC systems, addressing the challenges posed by the inherent segmentation of the grid and the integration of renewable energy sources l

关键词： VSC-MTDC VSG DC voltage MPC consensus algorithm SFD

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Distributed economic dispatch strategy of power system based on step-by-step V2G technology 4

Distributed economic dispatch strategy of power system based...

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4th International Conference on Informatics Engineering and Information Science (ICIEIS)

作者： Liu, Chuntao Song, Yunzhong Henan Polytech Univ Sch Elect Engn & Automat Jiaozuo Henan Peoples R China

ISBN: (数字)9781510651999

ISBN: (纸本)9781510651999;9781510651982

With the popularity of electric vehicles, the charging load increases gradually. A large number of disorderly connected electric vehicles will have a great impact on the power grid. Electric vehicle is a kind of schedulable energy storage resource with the dual characteristics of power supply and load, which has the ability of active regulation. In view of the above problems, using multi-agent consensus algorithm, taking the incremental cost of generator sets and the incremental benefit of aggregate electric vehicle as consensus variables, a strategy for aggregate electric vehicles to participate in power system economic dispatch is designed, and the economic dispatch problem is solved by distributed optimization. An example simulation is carried out on the IEEE 39 bus system, and the aggregate electric vehicles are connected to the power grid step-by-step to verify the effectiveness of the proposed strategy.

关键词： step-by-step aggregate electric vehicles distributed optimization economic dispatch consensus algorithm

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Comparison Experimental Analysis of Different Cryptocurrencies

Comparison Experimental Analysis of Different Cryptocurrenci...

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International Conference on Big Data, Information and Computer Network (BDICN)

作者： Fu, Dengrui Hu, Huiyun Xu, Yan Zheng, Kun Purdue Univ Dept Comp & Informat Technol W Lafayette IN 47907 USA Nanjing Univ Posts & Telecommun Bell Honors Sch Nanjing Peoples R China

ISBN: (纸本)9781665484763

Cryptocurrencies have proliferated in recent years, and all of them have more or less optimized the shortcomings of bitcoin. This paper selected four representative cryptocurrencies including LiteCoin, ETH, Zcash, and Ripple, and made a comprehensive comparison of their advantages and disadvantages, attacks and defenses and other aspects, based on reading a significant volume of relevant papers. The comprehensive comparison can more easily highlight the advantages of cryptocurrencies on the market so far, and more importantly, more vulnerabilities will be discovered and more defense methods will be interpreted, which must have certain guiding significance for the future vulnerability repair and defense against attacks of cryptocurrencies to a large extent. This will greatly improve the security of future cryptocurrencies. By analyzing their generation mode, their working mechanism, their security capabilities and their algorithms, the strengths and weaknesses of the four popular cryptocurrencies mentioned above can be summed up very clearly. On the basis of these pros and cons, it will be very easy to delineate where each cryptocurrency is suitable. In addition, potential vulnerabilities could be found by studying the consensus algorithm of each cryptocurrency. What we did was looking for possible attacks based on those vulnerabilities, and trying to find the appropriate defense methods. We have done a very thorough study of the work mentioned above, and have finally achieved a very detailed comparison of the differences between several cryptocurrencies. Finally, we came to the conclusion that each cryptocurrency has different styles in terms of advantages and features, and is relatively easy to spot in terms of weaknesses, making it vulnerable to some large-scale attacks. By comparing these cryptocurrencies in all aspects, a more secure and more powerful cryptocurrency may be created soon.

关键词： cryptocurrencies dust attack consensus algorithm working mechanism

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Federated Learning with Anomaly Client Detection and Decentralized Parameter Aggregation 52

Federated Learning with Anomaly Client Detection and Decentr...

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52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

作者： Shu Liu Shang, Yanlei Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China

ISBN: (数字)9781665402620

ISBN: (纸本)9781665402620

Federated learning is a framework for machine learning that is dedicated to data privacy protection. In federated learning, system cannot fully control the behavior of clients which can be faulty. These behaviors include sharing arbitrary faulty gradients and delaying the process of sharing due to Byzantine attacks or clients' own software and hardware failures. In federated learning, the parameter server may also be faulty during gradient collection and aggregation, mainly including gradient-based training data inference and model parameter faulty update. The above problems may lead to reduced accuracy of federated learning model training, leakage of client privacy, etc. Existing research enhances the robustness of federated learning by exploiting the decentralization and immutability of Blockchain. For untrusted clients, most research is based on Byzantine fault tolerance to defend against clients indiscriminately, and may cause model accuracy reduction. In addition, most of the research focus on unencrypted gradients, and there is insufficient research on dealing with client anomalies in the case of gradient encryption. For untrusted parameter servers, existing research has problems in energy overhead and scalability. Aiming at the problems above, this paper studies the robustness of federated learning, and proposes a blockchain-based federated learning parameter update architecture PUS-FL. Through experiments simulating distributed machine learning on neural networks, we demonstrate that the anomaly detection algorithm of PUS-FL outperforms conventional gradient filters including geometric median, Multi-Krum and trimmed mean. In addition, our experiments also verify that the scalability-enhanced parameter aggregation consensus algorithm proposed in this paper(SE-PBFT) improves consensus scalability by reducing communication complexity.

关键词： Federated learning Blockchain Trusted Computing Byzantine Attack consensus algorithm

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The resilience of the US banking system

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INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS 2022年第3期27卷 2819-2835页

作者： Papadimitriou, Theophilos Gogas, Periklis Agrapetidou, Anna Democritus Univ Thrace Dept Econ Komotini Greece

We investigate the resilience of the whole U.S. banking system (5,826 banks) over the period 2000-2018. In doing so, we employ a state-of-the-art bank failure forecasting model (Gogas et al., 2018) and we uncover the evolution of the safety margin from failure for all individual U.S. banks and the banking sector as a whole every year. We provide evidence that in recent years a lower competition and new regulations widened the safety margin of the banking system, resulting in a healthier financial sector as banks become less in total number but act more prudently.

关键词： consensus algorithm reputation‐ based consensus algorithm permissionless blockchain

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