Deep Auto-Encoder Based Intelligent and Secure Time Synchronization Protocol (iSTSP) for Security-Critical Time-Sensitive WSNs

Research output: Contribution to journalArticlepeer-review

Abstract

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 real-world 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-of-the-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.

Original languageEnglish
Pages (from-to)3213-3250
Number of pages38
JournalCMES - Computer Modeling in Engineering and Sciences
Volume144
Issue number3
DOIs
StatePublished - 2025

Bibliographical note

Publisher Copyright:
Copyright © 2025 The Authors.

Keywords

  • Internet of Things
  • Time-sensitive wireless sensor networks (TS-WSNs)
  • autoencoder model
  • deep learning
  • energy-efficient communication protocols
  • malicious node detection
  • secure time synchronization protocol
  • trust-based authentication

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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