Tampering with electronic measuring instruments poses a serious threat to transactional integrity, regulatory compliance, and public trust, particularly in cost-sensitive deployments, such as retail weighing systems. Existing protection mechanisms rely on either passive mechanical seals or isolated software checks, both of which are inadequate against coordinated physical and firmware-level attacks. This study presents T-SHIELD, a hybrid tamper-secure embedded architecture that integrates physical integrity sensing, firmware trust enforcement, and lightweight anomaly evaluation into a unified protection layer. Unlike recent solutions that emphasise computationally intensive machine learning, the proposed framework employs deterministic statistical intelligence tailored to resource-constrained embedded platforms. Experimental validation on a digital-weighing prototype demonstrated high tamper-detection accuracy, minimal false alarms, and negligible performance overhead. The results indicate that T-SHIELD offers a practical, regulation-friendly, and scalable solution for next-generation intelligent measurement instruments.