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02 / SENSOR SECURITY

When can we trust a sensor?

Conditional detectability of physical injection attacks on multimodal wearable sensing.

ROLE

Sole author

VENUE

ICICSP 2026

METHODS

Cross-modal detection · Statistical modeling

The question

A wearable system can receive signals that look like genuine motion even when a physical injection process has disturbed its inertial sensors. My research asks when an additional sensing modality can expose that inconsistency—and when detection remains limited.

My approach

  • Studied an inertial-only blind zone in which forged measurements can imitate genuine-motion distributions.
  • Used differently coupled barometer and magnetometer references for cross-modal consistency checking.
  • Derived a Mahalanobis-distance statistic, a chi-square decision rule, and a conditional detectability boundary.
Evaluation overview with model-based analysis and a FallAllD empirical path
Evaluation structure from the supplied portfolio.

Evidence and scope

The portfolio reports evaluation on FallAllD using leave-one-subject-out settings. For forged walking events, the magnetometer-reference detector achieved an AUC of 0.964. This number is specific to that evaluation setting.

Model-based reasoning and digitally emulated injection provide evidence about conditional detection. Physical-hardware validation, broader activity coverage, and generalization remain important directions for further evaluation.

Publication

Conditional Detectability of Physical Injection Attacks on Multimodal Wearable Sensing

Yuan Liao · Sole author · 2026 IEEE 9th ICICSP, Shanghai, September 18–20, 2026. The supplied proceedings contain the paper, and the conference certificate confirms an oral presentation.

Opening page of the ICICSP 2026 conference paper
Conference paper · opening page, printed page 276.
View proceedings and presentation evidence
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