Next Article in Journal
Towards Reliable and Energy-Efficient Incremental Cooperative Communication for Wireless Body Area Networks
Previous Article in Journal
Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(3), 281; doi:10.3390/s16030281

A New MAC Address Spoofing Detection Technique Based on Random Forests

Computer Science and Engineering Department, University of Bridgeport, 126 Park Ave, Bridgeport, CT 06604, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 21 December 2015 / Revised: 15 February 2016 / Accepted: 19 February 2016 / Published: 24 February 2016
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [690 KB, uploaded 24 February 2016]   |  

Abstract

Media access control (MAC) addresses in wireless networks can be trivially spoofed using off-the-shelf devices. The aim of this research is to detect MAC address spoofing in wireless networks using a hard-to-spoof measurement that is correlated to the location of the wireless device, namely the received signal strength (RSS). We developed a passive solution that does not require modification for standards or protocols. The solution was tested in a live test-bed (i.e., a wireless local area network with the aid of two air monitors acting as sensors) and achieved 99.77%, 93.16% and 88.38% accuracy when the attacker is 8–13 m, 4–8 m and less than 4 m away from the victim device, respectively. We implemented three previous methods on the same test-bed and found that our solution outperforms existing solutions. Our solution is based on an ensemble method known as random forests. View Full-Text
Keywords: MAC address; spoofing; detection; random forests; wireless sensor networks; wireless local area networks MAC address; spoofing; detection; random forests; wireless sensor networks; wireless local area networks
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Alotaibi, B.; Elleithy, K. A New MAC Address Spoofing Detection Technique Based on Random Forests. Sensors 2016, 16, 281.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top