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Secure Synchronization Control of Markovian Jump Neural Networks Under DoS Attacks with Memory-Based Adaptive Event-Triggered Mechanism
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作者 Shanshan ZHAO Linhao ZHAO +1 位作者 Shiping WEN Long CHENG 《Artificial Intelligence Science and Engineering》 2025年第1期64-78,共15页
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri... This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples. 展开更多
关键词 Piecewise-homogeneous Markovian process delay neural networks security synchronization control memory-based adaptive eventtriggered mechanism
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Deep Auto-Encoder Based Intelligent and Secure Time Synchronization Protocol(iSTSP)for Security-Critical Time-Sensitive WSNs
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作者 Ramadan Abdul-Rashid Mohd Amiruddin Abd Rahman Abdulaziz Yagoub Barnawi 《Computer Modeling in Engineering & Sciences》 2025年第9期3213-3250,共38页
Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade... Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols. 展开更多
关键词 Time-sensitive wireless sensor networks(TS-WSNs) secure time synchronization protocol trust-based authentication autoencoder model deep learning malicious node detection Internet of Things energyefficient communication protocols
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