@Article{jqc.2020.09433,
AUTHOR = {Ping Lu},
TITLE = {A Position Self-Adaptive Method to Detect Fake Access Points},
JOURNAL = {Journal of Quantum Computing},
VOLUME = {2},
YEAR = {2020},
NUMBER = {2},
PAGES = {119--127},
URL = {http://www.techscience.com/jqc/v2n2/40349},
ISSN = {2579-0145},
ABSTRACT = {In recent years, with the maturity and popularity of Wi-Fi technology, 
wireless hotspots have been deployed on a large scale in public places. But at the 
same time, it brings many security issues that cannot be ignored. Among them, the 
fake access point attack is a very serious threat in wireless local area network. In 
this paper, we propose a method to detect fake access points in wireless local area 
network. First, our detection method is passive, which means there is almost no 
additional traffic will be generated during the program’s operation. Second, 
different from many existing methods, our method allows the detection device to 
change position, the move will be perceived and the fingerprint will be updated 
automatically. Third, we use a variety of features as fingerprints to describe an 
access point better and improve efficiency. At last, the method we propose is more 
in line with the actual scene and has been proved effective by experiments.},
DOI = {10.32604/jqc.2020.09433}
}