LiquidAuth: reliable and accurate liquid authentication using GAN-enhanced acoustic-to-mass-spectrum mapping
Author(s)
Type
Conference Paper
Abstract
Counterfeit and adulterated liquids present significant health risks and economic losses, underscoring the need for effective authentication methods. While acoustic signal-based detection offers a promising non-invasive approach that works without opening containers, its accuracy suffers from variations in container properties and environmental conditions. Furthermore, acoustic features alone lack molecular-level detail needed for definitive identification. We address these challenges with LiquidAuth, a system that maps acoustic signals to mass spectra, providing molecular-level insights for more accurate authentication. LiquidAuth employs a cross-shaped microphone array to mitigate positional variation and introduces an adaptive container compensation algorithm to account for different container characteristics. By integrating Conditional GANs (cGANs), our system effectively maps acoustic signals to mass spectra, enabling reliable molecular-level classification. Experimental evaluations show LiquidAuth achieves an average F1-score of 97.89%, with accuracy between 95.35% and 98.25% across various container materials and storage conditions, demonstrating robust liquid authentication capabilities.
Date Issued
2025-08-29
Date Acceptance
2025-08-01
Citation
2025 34th International Conference on Computer Communications and Networks (ICCCN), 2025, pp.1-9
ISSN
1095-2055
Publisher
IEEE
Start Page
1
End Page
9
Journal / Book Title
2025 34th International Conference on Computer Communications and Networks (ICCCN)
Copyright Statement
© 2026 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Source
2025 34th International Conference on Computer Communications and Networks (ICCCN)
Publication Status
Published
Start Date
2025-08-04
Finish Date
2025-08-07
Coverage Spatial
Tokyo, Japan