What question did this study set out to answer?

The study aims to develop a deterministic fingerprinting method for identifying IoT devices based on network behavior.

April 14, 2026Open Access

IoT-ID: Deterministic Device Identity from Hybrid Network Fingerprinting

Key Points

The study aims to develop a deterministic fingerprinting method for identifying IoT devices based on network behavior.
Developed a fingerprinting system named IoT-ID for IoT device identification.
Combined passive and active network traffic measurements.
Utilized cryptographic hashing to derive device identities without training data.
Integrated application-layer metadata with transport-layer signatures for consistent identification.
Confirmed the effectiveness of deterministic device identification across IoT devices.
Showed limitations of the approach in non-IoT systems due to privacy mechanisms.
Highlighted the challenge of software homogeneity affecting identification.

Abstract

This paper presents IoT-ID, a deterministic fingerprinting system for IoT device identification based on network traffic analysis. By combining passive and active measurements into a canonical multi-layer representation and applying cryptographic hashing, IoT-ID derives stable and reproducible device identities without relying on training data. The integration of application-layer metadata with transport-layer signatures resolves collisions between devices with indistinguishable network stacks, enabling consistent identification across heterogeneous environments. Results confirm the feasibility and effectiveness of deterministic fingerprinting, while highlighting limitations in non-IoT systems due to privacy mechanisms and software homogeneity.

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