The Seven Habits of Highly Trustworthy Devices

By Srinivas Kumar
Chief Technology & Product Officer at Mocana Corporation

food production factory control IIoT device

Digital transformation of traditional original equipment manufacturer (OEM) product and solution offerings requires hardening of connected and edge devices with a horizontal platform that provides a "single pane of glass" for operational technology (OT) security.

Deploying greenfield devices in traditional network silos alongside legacy brownfield devices in OT environments introduces major risks and exposes a huge attack surface for cyber warfare.

The imminent threats – posed by the cybercrime syndicate and nation-state actors targeting critical infrastructure and unprotected devices – warrant establishing a trust chain for supply chain risk management as a collaborative effort between OEMs, brand name device vendors, and managed security service providers (MSSPs).

The primary goal of digital transformation should be to manufacture devices at scale for supply chain risk management and operational resilience with visibility and control for tamper-resistance, anti-cloning, and condition-based monitoring. The transformation must begin at the device. The passage to digital transformation requires all stakeholders to recognize the following realisms:

  • IIoT/IoT is an ecosystem that requires a horizontal platform.
  • A collaborative effort is required between OEMs, brand name device vendors, and MSSPs for cost-effective cyber protection as a service.
  • OT/IT convergence requires a paradigm shift.
  • Integration of emerging and emerged technologies for an epical (economical, political, intellectual, commercial) story.

With this as the context for digital transformation, the seven habits of highly trustworthy devices may be enumerated as follows.

1) Persistence of Trust

  • Establish and preserve device trustworthiness throughout the lifecycle.
  • Ensure that data harvested and processed for analytics by artificial intelligence (AI) and machine learning (ML) engines is trustworthy for safe and secure mission-critical decision logic and outcomes.

2) Reduces Lifetime Costs

  • Reduce the OEM’s and enterprise’s capital and operational expenses.
  • Scale and automate manufacturing, deployment, and lifetime monitoring of heterogeneous connected and edge devices.

3) Manages Supply Chain Risks

  • Manage supply chain risks with tamper-resistant content delivery.
  • Track and trace along the supply chain from the developer, though providers and publishers to the target OT device.

4)   Recovers to a Trusted State

  • Remotely orchestrate field device recovery and mitigate service outages.
  • Remotely rollback images and/or configurations to a trusted baseline.
  • Remotely rotate cryptographic artifacts (keys, certificates) to minimize exposure to potential exploits.

5) Protects Data in Custody

  • Protect data (at-rest, in-process, in-transit) in the custody of mission critical native and/or containerized applications.
  • Use a secure element as the hardware, firmware, or software-based root of trust.

6) Protects Digital Assets

  • Prevent theft of intellectual property and/or mission-critical data by untrusted devices.
  • Prevent cloning of trusted devices.

7) Achieves Compliance

  • Provide security controls required for compliance with emerging standards and certifications for cybersecurity and multi-vendor field device interoperability.
  • IEC 62443/61850, NIST 800-53/800-63-3, NERC CIP, FIPS 140-2/140-3, FCG.

Device Protection

Device protection is based on five pillars of risk: device identification, device authentication, key protection, data protection and operational trustworthiness. The security, safety, and economics of designing and implementing risk countermeasures in trustworthy devices will far outweigh the cost of innovation for key players in the IoT ecosystem.


In the rapidly emerging IoT industry segments, such as smart buildings, smart factories, smart cities and smart energy, there are revenue drivers and return on investment associated with transforming device management with applied data sciences and subscription-based cloud services.

Within the next two years, emerging 5G and secure element-enabled services (e.g. TPM, SIM) will lead to a proliferation of heterogeneous connected and edge devices in traditional enterprise-managed ecosystems, and present new challenges in OT/IT convergence and integration with cloud platform providers without vendor lock-in.

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