Authentication solutions used to combat counterfeits in the Internet of Things rely on different types of labels, and counterfeit activities have negative economic impacts on organizations. Solutions based on RFID tags have been widely adopted in various industries. However, RFID tags have different security issues and are vulnerable to attacks. Therefore, to overcome the limitations of the current security labels, new types must be developed and studies have been conducted on the usage of luminescent materials and labels. In this study, we propose a symmetric key and hash function-based authentication protocol for luminescent labels. We also propose new phosphorescent security labels whose time responses are excitation wavelength dependent and are created using seven strontium aluminate tags. The 365 nm and 385 nm UV LED excitation sources of the labels cause different RGB dependent time responses measurable by a smartphone at 30 FPS. The rise and decay time responses of the R(red), G(green), and B(blue) signals are separately analysed. Relative shares of the R, G, and B components are obtained by converting these signals into a series of numbers used as security codes to authenticate the labels.

In this paper, we propose a lightweight authentication and identification protocol based on different phosphorescent Strontium aluminate color labels. The excitation sources are pulsed UV LEDs emitting at 365 nm and 385 nm, causing different RGB-dependent time responses of the label that are measured using a smartphone recording at 30 FPS. The rise and decay time responses as measured by the red (R), green (G) and blue (B) pixels were separately analyzed and were found to follow a power law with individual parameters depending on the excitation wavelength, pulse duration and duty cycle, which serve as security features and are suitable for authentication purposes in IoT applications. Our solution uses simple cryptographic functions such as HMAC and XOR. We performed a security analysis of our protocol to prove its resistance to known attack vectors. The proposed scheme has minimal computation and communication costs and can be deployed on resource-constrained Internet of Things devices.