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February 25, 2026The Computer Journal0 citations

Efficient router fingerprinting in IPv6 networks

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YYYifan YangLHLing HuTYTao Yang

Key Points

  • The aim is to develop a robust method for identifying router vendors in IPv6 networks to enhance network visibility and security.
  • Introduced a lightweight fingerprinting methodology called IPv6 Router FingerPrinting (6RFP).
  • Analyzed EUI-64 interface identifiers for vendor-specific patterns in IPv6 addresses.
  • Profiled IPv6 Identification Field characteristics to differentiate vendor implementations.
  • Evaluated the methodology across various network environments.
  • Achieved 85.79% accuracy in router vendor identification.
  • Demonstrated an 86.01% improvement over existing techniques.
  • Maintained minimal computational overhead for real-time deployment.

Abstract

Abstract The pervasive interconnection of heterogeneous routing devices forms the fundamental infrastructure of modern Internet communication, making accurate router vendor identification a critical capability for multiple domains including network topology mapping, intelligent traffic engineering, and proactive cybersecurity defense. While Internet Protocol version 6 (IPv6) has achieved widespread global deployment as the next-generation Internet protocol, the opaque nature of its addressing mechanisms and protocol behaviors has created significant challenges in router attribute detection across IPv6 networks, leaving a crucial gap in network visibility and security analytics. To address this pressing challenge, we present IPv6 Router FingerPrinting (6RFP), an innovative lightweight fingerprinting methodology that establishes a new paradigm for IPv6 router vendor identification by systematically combining two complementary analytical dimensions: (i) comprehensive EUI-64 interface identifier analysis that captures vendor-specific hardware encoding patterns embedded in IPv6 addresses, and (ii) sophisticated IPv6 Identification Field characteristic profiling that reveals distinctive vendor implementations. Through extensive evaluation across diverse network environments, 6RFP demonstrates highly effective detection capabilities, achieving 85.79% accuracy—representing a remarkable 86.01% improvement over current state-of-the-art techniques—while maintaining minimal computational overhead suitable for real-time deployment.

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Cite This Study

Yang et al. (2026) studied this question.

synapsesocial.com/papers/699e919cf5123be5ed04f3e4https://doi.org/10.1093/comjnl/bxag004
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