12.3 Exploring PUF-Controlled PA Spectral Regrowth for Physical-Layer Identification of IoT Nodes
Authors:
- 13 February 2021
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 64, 204-206
Abstract
It is projected that 75 billion Internet-of-Things (IoT) devices will be deployed for applications such as wearable electronics and smart home by 2025. Securing IoT devices is one of the most significant barriers we need to overcome for large-scale IoT adoption. Conventional wireless security has been implemented solely using upper-layer cryptography [1]. Unfortunately, IoT nodes are often energy-constrained and may not have enough computational resources to implement advanced asymmetric cryptographic algorithms and public-key-infrastructures (PKI) [2]–[3]. To overcome this challenge, there has been growing interest in leveraging the physical impairments of the radios that are bonded to specific TX for secure identification [4] –[6], a.k.a. RF fingerprinting. If Bob (the RX) has sufficient sensitivity, it can identify Alice (the legitimate TX) and the malicious impersonator during demodulation based on their inherent radio signatures, similar to how we distinguish different people based on their unique voice signatures (Fig. 12.3.1). As the device-dependent radio impairments come from process variation, it is challenging for impersonators to forge in practice. In addition, unlike conventional identification approach that device IDs are inserted in preambles and checked only once a while, RF fingerprinting enables continuous identification at any moment during communication, leading to a tighter bond between the data packet and device.Keywords
This publication has 9 references indexed in Scilit:
- A 0.2-V Energy-Harvesting BLE Transmitter With a Micropower Manager Achieving 25% System Efficiency at 0-dBm Output and 5.2-nW Sleep Power in 28-nm CMOSIEEE Journal of Solid-State Circuits, 2019
- RF-PUF: IoT security enhancement through authentication of wireless nodes using in-situ machine learning2018
- A Fully Integrated Bluetooth Low-Energy Transmitter in 28 nm CMOS With 36% System Efficiency at 3 dBmIEEE Journal of Solid-State Circuits, 2016
- Physical Layer Authentication for Mobile Systems with Time-Varying Carrier Frequency OffsetsIEEE Transactions on Communications, 2014
- A WLAN RF CMOS PA With Large-Signal MGTR MethodIEEE Transactions on Microwave Theory and Techniques, 2013
- ESIP: Secure Incentive Protocol with Limited Use of Public-Key Cryptography for Multihop Wireless NetworksIEEE Transactions on Mobile Computing, 2010
- Securing wireless systems via lower layer enforcements2006
- Security in wireless sensor networks: issues and challenges2006
- A study of the energy consumption characteristics of cryptographic algorithms and security protocolsIEEE Transactions on Mobile Computing, 2005