Domain-Agnostic Hardware Fingerprinting-Based Device Identifier for Zero-Trust IoT Security

Next-generation networks aim for comprehensive connectivity, interconnecting humans, machines, devices, and systems seamlessly. This interconnectivity raises concerns about privacy and security, given the potential network-wide impact of a single compromise. To address this challenge, the Zero Trust (ZT) paradigm emerges as a key method for safeguarding network integrity and data confidentiality. This work introduces EPS-CNN, a novel deep-learning-based wireless device identification framework designed to serve as the device authentication layer within the ZT architecture, with a focus on resource-constrained IoT …

address aim challenge compromise confidentiality connectivity cs.cr cs.ni data device devices domain eess.sp fingerprinting hardware humans impact integrity iot iot security key machines network networks next paradigm privacy privacy and security security single systems trust zero trust