There's Waldo: PCB Tamper Forensic Analysis using Explainable AI on Impedance Signatures

Tampered electronics can now be identified non-invasively: The research demonstrates that tampering with circuit board components can be detected and located by analyzing electrical impedance signatures without physically opening or damaging devices, making this approach practical for real-world security verification.

AI transparency is crucial for security applications: The study uses explainable AI (XAI) techniques to show why the system flags a component as tampered, not just that it's tampered. By employing SHAP values to identify which specific frequency patterns trigger alerts, the approach enables human experts to verify and understand the AI's reasoning rather than treating it as a "black box."

High accuracy with practical implications: The random forest classifier achieved 96.7% accuracy in detecting tampering, suggesting this method could be reliably deployed to protect supply chains from counterfeit or maliciously modified components before they reach consumers.

Supply chain security has become a technical priority: The paper addresses a growing vulnerability in electronics manufacturing where components can be secretly altered during production or distribution, highlighting why automated forensic tools are increasingly necessary for national security and consumer safety.