  Node forgery or impersonation, in which legitimate cryptographic credentials
are captured by an adversary, constitutes one major security threat facing
wireless networks. The fact that mobile devices are prone to be compromised and
reverse engineered significantly increases the risk of such attacks in which
adversaries can obtain secret keys on trusted nodes and impersonate the
legitimate node. One promising approach toward thwarting these attacks is
through the extraction of unique fingerprints that can provide a reliable and
robust means for device identification. These fingerprints can be extracted
from transmitted signal by analyzing information across the protocol stack. In
this paper, the first unified and comprehensive tutorial in the area of
wireless device fingerprinting for security applications is presented. In
particular, we aim to provide a detailed treatment on developing novel wireless
security solutions using device fingerprinting techniques. The objectives are
three-fold: (i) to introduce a comprehensive taxonomy of wireless features that
can be used in fingerprinting, (ii) to provide a systematic review on
fingerprint algorithms including both white-list based and unsupervised
learning approaches, and (iii) to identify key open research problems in the
area of device fingerprinting and feature extraction, as applied to wireless
security.
