SLFAT: Client-Side Evil Twin Detection Approach Based on Arrival Time of Special Length Frames

Abstract

In general, the IEEE 802.11 network identifiers used by wireless access points (APs) can be easily spoofed. Accordingly, a malicious adversary is able to clone the identity information of a legitimate AP (LAP) to launch evil twin attacks (ETAs). The evil twin is a class of rogue access point (RAP) that masquerades as a LAP and allures Wi-Fi victims' traffic. It enables an attacker with little effort and expenditure to eavesdrop or manipulate wireless communications. Due to the characteristics of strong concealment, high confusion, great harmfulness, and easy implementation, the ETA has become one of the most severe security threats in Wireless Local Area Networks (WLANs). Here, we propose a novel client-side approach, Speical Length Frames Arrival Time (SLFAT), to detect the ETA, which utilizes the same gateway as the LAP. By monitoring the traffic emitted by target APs at a detection node, SLFAT extracts the arrival time of the special frames with the same length to determine the evil twin's forwarding behavior. SLFAT is passive, lightweight, efficient, hard to be escaped. It allows users to independently detect ETA on ordinary wireless devices. Through implementation and evaluation in our study, SLFAT achieves a very high detection rate in distinguishing evil twins from LAPs.