On the Security of IoT Sensors

Devante Gray

Research output: ThesisDoctoral Thesis


This dissertation presents novel and practical security solutions at hardware and software levels to identify and harness new sources of information for resource and input-constrained IoT devices, whilst making use of the ubiquitous and readily available sensors present in the environments where these devices can be found. The solutions in this document are presented in the form of two distinct research projects.

SenSig: This work takes advantage of the output of the runtime calibration process that occurs within motion sensors, specifically gyroscopes, at startup. This output is used to create a unique identifier (i.e., a hardware fingerprint) which can then be used for authentication purposes. Due to the nature of the data used in the creation of the fingerprints, they can serve additional use cases, such as detecting device tampering, and functioning as an early warning system for the inevitable performance degradation of the sensors.

Photon Key: This work provides a solution to the device pairing problem present in IoT environments, by taking advantage of ambient light sensors for key generation purposes. Ambient light sensors are used to harness the information found in the various properties of light to enable two co-located devices with no prior shared secret to individually generate identical key material in a non-private environment.

The findings of these projects demonstrate how security solutions that factor in the unique constraints of IoT environments can be implemented using readily available resources: sensors in emerging technologies.
Original languageEnglish
Awarding Institution
  • Royal Holloway, University of London
  • Mehrnezhad, Maryam, Supervisor
Thesis sponsors
Award date1 Apr 2024
Publication statusUnpublished - 2024


  • IoT
  • Hardware Security
  • Sensors
  • Resource Constrained Devices
  • Device Pairing
  • Fuzzy Cryptography
  • Fingerprinting
  • Engineering

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