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Editorial

Research on IPV6 Network Security Intrusion Detection Algorithm based on parallel multipath

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  • @ARTICLE{10.4108/eetsis.11206,
        author={Qingyun Dong and Manzeng Ma and Linnan Zhu and Hao Zhang},
        title={Research on IPV6 Network Security Intrusion Detection Algorithm based on parallel multipath},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={13},
        number={1},
        publisher={EAI},
        journal_a={SIS},
        year={2026},
        month={7},
        keywords={Intrusion Detection Algorithms, Network Security, Internet Protocol Version 6, Wireless Sensor Networks},
        doi={10.4108/eetsis.11206}
    }
    
  • Qingyun Dong
    Manzeng Ma
    Linnan Zhu
    Hao Zhang
    Year: 2026
    Research on IPV6 Network Security Intrusion Detection Algorithm based on parallel multipath
    SIS
    EAI
    DOI: 10.4108/eetsis.11206
Qingyun Dong1, Manzeng Ma1,*, Linnan Zhu1, Hao Zhang1
  • 1: Cangzhou Normal University
*Contact email: mamanzeng@caztc.edu.cn

Abstract

Internet Protocol Version 6 (IPv6) enables large-scale connectivity for wireless sensor networks (WSNs), allowing resource-constrained sensing nodes to interact directly with external Internet services. However, this open connectivity significantly increases the exposure of IPv6-based WSNs to diverse cyber threats originating from both local networks and the public Internet. Existing intrusion detection systems (IDS) designed for traditional networks often struggle to operate effectively in IPv6 WSN environments due to limited node resources, high traffic dimensionality, and the dynamic characteristics of sensor communication. To address these limitations, this paper proposes an intrusion detection algorithm for IPv6 wireless sensor networks based on a parallel multipath detection framework. The proposed approach integrates a hierarchical security architecture, a generalized information modeling mechanism, and feature-driven anomaly detection to improve detection efficiency while maintaining lightweight computational overhead. By organizing traffic features through structured data preprocessing and adaptive decision rules, the method enables efficient identification of abnormal network behavior in resource-constrained environments. Experimental evaluation based on simulated IPv6 WSN traffic and the UNSW-NB15 dataset demonstrates that the proposed algorithm achieves fast detection performance with an average detection time of 0.12–0.14 μs per sample. The results indicate that the proposed approach can effectively support real-time intrusion detection in IPv6 wireless sensor networks while maintaining low computational cost.

Keywords
Intrusion Detection Algorithms, Network Security, Internet Protocol Version 6, Wireless Sensor Networks
Received
2026-12-03
Accepted
2026-04-14
Published
2026-07-22
Publisher
EAI
http://dx.doi.org/10.4108/eetsis.11206

Copyright © 2026 Qingyun Dong et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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