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Overview

In today’s threat landscape, verifying the authenticity of image data is critical — especially in domains like aerospace, defense, and IoT. A single tampered image can mislead systems or operators, with potentially catastrophic consequences. At Vortex, we’ve developed a cybersecurity solution that enables hardware-based image authentication without modifying the physical device. Leveraging Physical Unclonable Functions (PUFs), we use each device’s natural manufacturing variations to create a unique digital signature. This allows for real-time validation of data integrity at the source — from the camera to the cloud.

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Challenge

Data producers are facing challenges with guaranteeing the authenticity of their data, especially for image-producing systems due to the increase in quality of AI-based image creating and modification systems. Since the image capturing systems do not include cryptographic operations, these industries face the challenge of how to retrofit the existing systems with cost-effective methods to provide security guarantees, such as integrity.

Solution

The Physical Unclonable Functions-based (PUF) authentication is used to sign a bit stream coming from a board; the signature is created by the board’s firmware. A bit stream can be the output of a CMOS camera sensor, a seismography sensor, a home automation actuator, etc.

Key aspects of the PUF authentication solution include:

  • Unique Signature Creation: During manufacturing, chips retain small differences. PUFs explore these differences to create a unique signature for each chip, requiring a specialized circuit.
  • Authentication of Device Outputs: This unique signature can be used to authenticate the outputs of the device, ensuring data integrity.
  • Challenge-Response Pairs: Data exchanges using this technique require challenge-response pairs. The receiver issues a challenge to the device, which is used to create the signature that is appended to the data.

These features ensure that the authenticity of image data is verified in real-time, from the camera to the cloud, without modifying the physical device.

Use Cases & Industry Applications

  • Satellite Imaging
    Authenticate that a satellite image was captured by the device it claims — ensuring integrity throughout transmission to base stations.
  • Photography & Cameras
    Guarantee an image was captured by a physical camera and not generated or altered by AI. Especially relevant for journalism, law enforcement, or evidence handling.
  • Internet of Things (IoT)
    Extend authentication capabilities to low-power devices that lack cryptographic hardware — such as home automation sensors or industrial controllers.
  • Connected Vehicles
    Enable vehicle cameras to report trusted observations in real-time — helping prevent spoofing attacks at intersections or on autonomous driving systems.

Results

  • Verified image provenance: Confirms that every image originated from a specific, untampered device at the time of capture.
  • Seamless integration: Easily added to existing systems through a firmware update, with no hardware redesign required.
  • Robust tamper prevention: Combines challenge-response, nonces, and device-unique hashes to eliminate the risk of forgery or replay attacks.
  • Hardware-agnostic security: Brings cryptographic assurances to devices without built-in cryptographic modules, enabling retroactive protection.
  • Cross-domain applicability: Scales from low-power IoT devices to satellite imaging systems without performance or cost penalties.
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