Telemetry data based counterfeit device detection

Abstract

Techniques are described for detecting counterfeit products by identifying differences between hardware components and orientations of the counterfeit products, and hardware components and orientations of authentic products. In some examples, the hardware components and orientations can be identified by generating hardware intrinsic development data based on telemetry data of products (or 'devices'). By way of example, the telemetry data may be analyzed by machine learning (ML) models to generate representative models of the hardware intrinsic development data. In various examples, the representative models can include sample representative models of hardware intrinsic development data generated based on valid telemetry data of authentic devices. In those or other examples, the representative models can include other representative models (or “test representative models”) of hardware intrinsic development data generated based on unvalidated telemetry data of test devices. Comparisons between the representative models can be utilized to identify the counterfeit products.