Cybersecurity in Smart Metrology – Safeguarding Data Integrity in Connected Systems
The rapid adoption of Smart Metrology – where measurement systems are networked, automated, and tightly integrated into digital manufacturing ecosystems – is transforming quality assurance. Measurement data now feeds directly into closed-loop process control, digital twins, analytics platforms, and enterprise systems, making metrology a core driver of modern manufacturing performance.
However, this growing connectivity also introduces new vulnerabilities. As measurement data increasingly drives high-value manufacturing decisions, cybersecurity has become a critical pillar of modern metrology. Protecting data integrity is no longer just an IT concern; it is fundamental to trust, compliance, and operational resilience.
Why Cybersecurity Matters in Metrology
Smart metrology systems underpin some of the most critical manufacturing functions, including:
- Real-time process control, where measurement results trigger automated machine adjustments
- Quality assurance and regulatory compliance, particularly in highly regulated industries
- Analytics and AI, which depend on clean, trustworthy datasets to deliver reliable insight
If measurement data is compromised through manipulation, loss, or unauthorised access, the consequences can be severe. Incorrect quality decisions, undetected defects, regulatory exposure, and reputational damage can all result. In connected environments, measurement systems are no longer isolated instruments; they form part of a much broader digital attack surface spanning production, quality, and enterprise systems.
Common Threat Vectors in Smart Metrology
Network-Based Attacks: Connected metrology systems frequently communicate via Ethernet, industrial networks, or wireless links. Poor segmentation or weak authentication can expose them to interception, spoofing, or unauthorised access.
Endpoint Vulnerabilities: Modern measurement devices often run embedded operating systems and complex firmware. Without disciplined patching and hardening, endpoints can become entry points for attackers.
Cloud and Data Platform Risks: As quality data is increasingly stored and analysed in cloud environments, misconfigured access controls or exposed credentials can compromise traceability and long-term data integrity.
Supply Chain Exposure: Metrology systems integrate software libraries, drivers, and third-party components. Vulnerabilities introduced through suppliers can propagate rapidly across connected systems.
As Smart Metrology becomes increasingly automated and autonomous, the integrity of measurement data takes on an even greater strategic importance. In environments where inline inspection systems, networked CMMs, and sensor-based measurement technologies feed directly into statistical process control and adaptive manufacturing systems, any compromise in data reliability can propagate rapidly across production. False or manipulated measurement results may not only affect individual parts, but also distort process trends, invalidate control limits, and mislead AI-driven optimisation tools. In this context, cybersecurity is inseparable from measurement uncertainty, traceability, and confidence in results—making data protection a fundamental requirement for maintaining control over modern, digitally driven manufacturing processes.
Lessons from the Jaguar Land Rover Cybersecurity Breach
The risks of interconnected manufacturing systems were starkly illustrated by the recent cybersecurity breach at Jaguar Land Rover (JLR). The attack forced the automotive manufacturer to shut down critical IT systems and temporarily halt production across multiple facilities, with significant operational and financial consequences.
While the incident was not specific to metrology systems, it highlights a crucial reality for quality and measurement professionals: in highly integrated digital factories, no system exists in isolation. Production, quality, logistics, and enterprise platforms are tightly coupled, meaning a breach in one domain can cascade rapidly across others.
For smart metrology, the implications are clear:
- Measurement systems connected to MES, ERP, and analytics platforms share the same digital risk environment.
- Compromised data integrity in inspection results could lead to incorrect pass/fail decisions, flawed process adjustments, or the release of non-conforming parts.
- Supply chain impacts extend beyond the OEM, affecting suppliers, calibration providers, and partners who rely on shared quality data.
- Operational disruption, rather than data theft alone, is often the most damaging outcome in manufacturing-focused cyberattacks.
Cybersecurity as a Core Element of Measurement Integrity
The Jaguar Land Rover incident serves as a powerful reminder that cybersecurity failures can quickly become “quality failures.” As Smart Metrology becomes more deeply embedded in production workflows – feeding automated decisions, digital twins, and AI models – it must be protected with the same rigour as safety-critical manufacturing systems.
From a governance perspective, securing Smart Metrology systems requires alignment with established industrial cybersecurity and information security standards. Frameworks such as IEC 62443, which addresses security for industrial automation and control systems, and ISO/IEC 27001, focused on information security management, provide structured guidance for managing risk across connected measurement environments. Applying these standards to metrology helps ensure consistent access control, secure data handling, and auditable processes across the entire measurement lifecycle – from data capture and transmission to storage and analysis. Crucially, governance should define clear ownership of metrology data security, bridging the traditional gap between IT, OT, and quality functions, and embedding cybersecurity responsibilities into quality management systems rather than treating them as a separate technical concern.
As metrology continues to evolve into a fully connected, data-driven discipline, cybersecurity must be recognised as an essential component of measurement integrity. By adopting layered security approaches, aligning with recognised industrial cybersecurity standards, and treating metrology data as a critical digital asset, manufacturers can protect not only their systems – but the trust placed in every measurement they make.
Author: Gerald Jones Editorial Assistant
