拒绝服务攻击下cucker - small系统群集的时间和能量成本

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Yongzheng Sun,Hailan Yang,Xiangxin Yin,Guanghui Wen,Chunyu Yang
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引用次数: 0

摘要

本文研究了拒绝服务(DoS)攻击如何影响与C-S系统中出现的群集动态相关的时间和能源成本(ec)。我们提出了弹性有限时间和固定时间的控制协议,并建立了cucker - small (C-S)系统在有限时间内实现群集的条件。攻击模式是随机建模的,并受攻击有效持续时间的约束。导出了时间和ECs的显式上界,表明它们不仅与组大小和控制参数有关,而且与DoS攻击的持续时间有关。理论分析和数值模拟一致表明,攻击持续时间越短,收敛速度越快,能耗越低。此外,我们的分析揭示了在DoS攻击下TC和EC之间的权衡,这表明应该仔细调整最佳通信强度,以满足实际应用的特定性能要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time and Energy Costs for Flocking of Cucker-Smale System Under Denial-of-Service Attacks.
This article investigates how Denial-of-Service (DoS) attacks impact the time and energy costs (ECs) associated with the emergence of flocking dynamics in the C-S system. We propose resilient finite-time and fixed-time control protocols against DoS attacks and establish conditions under which the Cucker-Smale (C-S) system can achieve flocking within a bounded time. The attack patterns are modeled stochastically and are constrained by the effective duration of the attack. Explicit upper bounds for both time and ECs are derived, demonstrating their dependence not only on the group size and control parameters, but also on the duration of DoS attacks. Theoretical analysis and numerical simulations consistently demonstrate that shorter attack durations facilitate faster convergence and lower energy consumption. Additionally, our analysis uncovers a tradeoff between TC and EC under DoS attacks, suggesting that optimal communication intensity should be carefully adjusted to meet specific performance requirements of practical applications.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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