Domain-Adaptive Device Fingerprints for Network Access Authentication Through Multifractal Dimension Representation. (arXiv:2308.07925v1 [cs.CR])

RF data-driven device fingerprinting through the use of deep learning has
recently surfaced as a potential solution for automated network access
authentication. Traditional approaches are commonly susceptible to the domain
adaptation problem where a model trained on data from one domain performs badly
when tested on data from a different domain. Some examples of a domain change
include varying the device location or environment and varying the time or day
of data collection. In this work, we propose using multifractal …

access authentication automated data data-driven deep learning device domain fingerprinting fingerprints network network access problem representation solution