EM-ID: Tag-less Identification of Electrical Devices via Electromagnetic Emissions

We present a low cost method for extracting the EM-ID from a device along with a new classification and ranking algorithm that is capable of identifying minute differences in the EM signatures.

Radio Frequency Identification technology has greatly improved asset management and inventory tracking. However, for many applications RFID tags are considered too expensive compared to the alternative of a printed bar code, which has hampered widespread adoption of RFID technology. To overcome this price barrier, our work leverages the unique electromagnetic emissions generated by nearly all electronic and electromechanical devices as a means to individually identify them. This tag-less method of radio frequency identification leverages previous work showing that it is possible to classify objects by type (i.e. phone vs. TV vs. kitchen appliance, etc.). A core question is whether or not the electromagnetic emissions from a given model of device, is sufficiently unique to robustly distinguish it from its peers. We present a low cost method for extracting the EM-ID from a device along with a new classification and ranking algorithm that is capable of identifying minute differences in the EM signatures. Results show that devices as divers as electronic toys, cellphones and laptops can all be individually identified with an accuracy between 72% and 100% depending on device type. While not all electronics are unique enough for individual detection, we present a probability estimation model that accurately predicts the performance of identifying a given device out of a population of both similar and dissimilar devices. Ultimately, EM-ID provides a zero cost method of uniquely identifying, potentially billions of electronic devices using their unique electromagnetic emissions.