SummaryThis paper proposes a passive user‐side solution, called Wi‐Fi legal access point (AP) finder (LAF), to the notorious evil twin access point problem, which in turn can result in diverse security problems, such as fraud, identity theft, and man‐in‐the‐middle attacks. Due to the severe security threats created by evil twins, many promising solutions have been proposed. However, the majority of these solutions are designed for the administrators of wireless networks, not for Wi‐Fi users. Hence, they are either too expensive or need some data that are usually not accessible to normal users. LAF utilizes the TCP three‐way handshake‐related packets and packet forwarding property created by evil twins to find legal APs, called good twins, at public hotspots or unencrypted WLANs; thus, it does not need any data or assistance from wireless network administrators. LAF does not send exploring packets actively; hence, evil twins cannot sense its existence. No matter when and where a user needs to utilize an AP to connect to the Internet at a hotspot, he can just use LAF to find out a legal AP to connect to. Experimental results show that LAF can quickly and accurately find legal APs after observing only a few packets.
An evil twin is a kind of rogue Wi-Fi access point (AP) which has the same SSID name to the legitimate one and is set up by an adversary. The user who associates to the evil twin, adversary may eaves-drops sensitive data on wireless communications to the Internet. Most of existing detection solutions are administrator-based, which is used by wireless network administrator to verify whether a given AP is in an authorized list or not. Such administrator-based solutions are limited, hardly maintained, and difficult to protect users timely when the attack is launched. Hence, we propose a client-based detection by operating the wireless network interface controller (WNIC) in monitor mode and capturing the Internet packets. Through analyzing the captured packets, client users can easily and precisely detect the evil twin attack even in a complicated AP scenario as well as avoid any threat arisen from connecting to an AP. Our method does not need to know any authorized AP list, and does not rely on data training or machine learning technique of target wireless network. Finally, we implemented a detecting system on Windows 7, which is widely used nowadays.
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