Device Fingerprinting in Wireless Networks: Challenges and Opportunities

dc.contributor.authorXu, Qiang
dc.contributor.authorZheng, Rong
dc.contributor.authorSaad, Walid
dc.contributor.authorHan, Zhu
dc.date.accessioned2020-05-11T16:15:00Z
dc.date.available2020-05-11T16:15:00Z
dc.date.issued9/3/2015
dc.description.abstractNode 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.
dc.identifier.citationCopyright 2015 IEEE Communications Surveys & Tutorials. This is a pre-print version of a published paper that is available at: https://ieeexplore.ieee.org/abstract/document/7239531. Recommended citation: Xu, Qiang, Rong Zheng, Walid Saad, and Zhu Han. "Device fingerprinting in wireless networks: Challenges and opportunities." IEEE Communications Surveys & Tutorials 18, no. 1 (2015): 94-104. DOI: 10.1109/COMST.2015.2476338. This item has been deposited in accordance with publisher copyright and licensing terms and with the author's permission.
dc.identifier.urihttps://hdl.handle.net/10657/6454
dc.publisherIEEE Communications Surveys & Tutorials
dc.subjectWireless security
dc.subjectdevice fingerprint
dc.subjectsupervised learning
dc.subjectunsupervised learning
dc.titleDevice Fingerprinting in Wireless Networks: Challenges and Opportunities
dc.typeArticle

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