• DocumentCode
    3039403
  • Title

    Rogue Access Point Detection by Analyzing Network Traffic Characteristics

  • Author

    Shetty, Sachin ; Song, Min ; Ma, Liran

  • Author_Institution
    Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529
  • fYear
    2007
  • fDate
    29-31 Oct. 2007
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    One of the most challenging network security concerns for network administrators is the presence of rogue access points. Rogue access points, if undetected, can be an open door to sensitive information on the network. Many data raiders have taken advantage of the undetected rogue access points in enterprises to not only get free Internet access, but also to view confidential information. Most of the current solutions to detect rouge access points are not automated and are dependent on a specific wireless technology. In this paper, we present a rogue access point detection approach. The approach is an automated solution which can be installed on any router at the edge of a network. The main premise of our approach is to distinguish authorized WLAN hosts from unauthorized WLAN hosts connected to rogue access points by analyzing traffic characteristics at the edge of a network. Simulation results verify the effectiveness of our approach in detecting rogue access points in a heterogeneous network comprised of wireless and wired subnets.
  • Keywords
    Communication system security; Frequency; Information security; Monitoring; Personnel; Telecommunication traffic; Traffic control; Wireless LAN; Wireless networks; Wireless sensor networks; Rogue access point; detection; traffic characteristics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Military Communications Conference, 2007. MILCOM 2007. IEEE
  • Conference_Location
    Orlando, FL, USA
  • Print_ISBN
    978-1-4244-1513-7
  • Electronic_ISBN
    978-1-4244-1513-7
  • Type

    conf

  • DOI
    10.1109/MILCOM.2007.4455018
  • Filename
    4455018