Physical Layer Authentication for Extending Battery Life - Ayyildiz, Cem; Cetin, Ramazan; Khodzhaev, Zulfidin; Kocak, Taskin; Soyak, Ece Gelal; Gungor, V. Cagri; Kurt, Gunes Karabulut (Elsevier, 2021)
Increasing population density in cities, and the increasing demand for efficiency in resource usage call for architectures enabling smart cities, such as the Internet of Things (IoT). In most such scenarios, the data generated by IoT sensors is not confidential, but its integrity is critical. Data integrity can be achieved by establishing certification mechanisms that provide cryptographic message authentication protocols; however, this requires relatively expensive components for storing and processing the encryption key on the sensor and consumes more power while processing and transmitting data, which leads to the renunciation of security issues in cost sensitive deployments. In this paper, we propose a security solution that provides data integrity without draining the batteries of IoT sensors. Our solution consists of, (i) differentiating legitimate sensors by taking advantage of their impurities formed during the manufacturing process of the transceiver components, and (ii) eliminating the complex components that carry out cryptography as well as the redundant packet header fields, thereby yielding power savings. The testbed implementation of the proposed solution yields power measurement results providing an estimate of 2.52 times improvement in battery life without compromising the integrity of communications in the system, in addition to offering an increase in spectral efficiency and a decrease in the overall IoT device cost.
Gelal Soyak, Ece/0000-0003-2410-6267; Cetin, Ramazan/0000-0002-5371-3106; Ayyildiz, Cem/0009-0009-7297-916X;
Keywords: Internet of Things (IoT); Smart City; Physical Layer Security; Rf Fingerprinting; Battery Life; Convolutional Neural Networks (Cnn); Energy Efficient