Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

A Method for Detecting 802.11 Wireless Malicious Phishing Stations through Fingerprinting

Authors
Na Lv, Jianguo Jiang, Haitao Zhu
Corresponding Author
Na Lv
Available Online May 2018.
DOI
10.2991/ncce-18.2018.119How to use a DOI?
Keywords
WLAN; MAC; OSI; legitimate devices; fingerprinting.
Abstract

Malicious phishing stations, which disguise as legitimate devices through MAC address forgery, constitute a lot of Wireless Local Area Network (WLAN) security threats, such as secret information theft, implantation of Trojans and backdoors, etc. In this paper, a passive method based on wireless fingerprinting for detecting malicious phishing stations is proposed. We design 11 dimensions of features of station's fingerprinting, which can be extracted from frames and packets on MAC layer and application layer of open system interconnection (OSI) protocol stack. We have monitored wireless traffic above 60 hours and collected more than 10GB data in a real scenario to fingerprint all stations for recognizing phishing stations. We also evaluate the performance of proposed method by considering precision, recall, false positives and false negatives. The results show that our method has good performance that can detect phishing stations effectively and our method is also scalable.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
Series
Advances in Intelligent Systems Research
Publication Date
May 2018
ISBN
978-94-6252-517-7
ISSN
1951-6851
DOI
10.2991/ncce-18.2018.119How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Na Lv
AU  - Jianguo Jiang
AU  - Haitao Zhu
PY  - 2018/05
DA  - 2018/05
TI  - A Method for Detecting 802.11 Wireless Malicious Phishing Stations through Fingerprinting
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 727
EP  - 732
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.119
DO  - 10.2991/ncce-18.2018.119
ID  - Lv2018/05
ER  -