Inferring user relationship from hidden information in WLANs

Abstract

Abstract-With ever increasing usage of handheld devices and vast deployment of wireless networks, we observe that it is possible to collect data from mobile devices and reveal personal relationships of their owners. In the paper, we exploit the hidden information collected from WLAN devices and infer individual relationships between device pairs based on three observation dimensions: network association history, physical proximity and spatio-temporal behavior. By measuring WLAN data, we demonstrate that device owners with social relationship tend to share access points, or show similar behavior patterns in wireless communications (e.g. go to the same place periodically to access the same WLAN network). These results can be exploited for various network analytic purposes.

SSIDs in the wild: Extracting semantic information from WiFi SSIDs

“…Apps can get information about the user's current network or can collect a snapshot of networks user's have connected in the past by accessing the preferred network list [5] and that enables building a user profile instantly. Some WiFi enabled smartphones send out probe requests to the networks they have connected in the past [7], [8], [9] and an adversary who monitors the wireless channel can easily collect this information.…”

“…Multiple work have studied privacy leakages related to WiFi connectivity in Smartphones [7], [8], [9], [5]. Greenstein et al [7] presented the privacy issues of 802.11 service discovery, that results in the device MAC address as well as the identifiers (SSID) of previously connected networks being leaked on the wireless channels.…”

“…Cunche et al [8] showed that SSIDs leaked by wireless devices can be used to infer social links between the owners. Cheng et al [9] extended this sociallink inference framework by including physical proximity and spatio-temporal behaviour. Achara et al [5] investigated the abuse of the Wi-Fi related permission of the Android system and showed that it can be exploited by apps to obtain sensitive information such as users' location.…”

Building up knowledge through passive WiFi probes

“…Cheng et al show in [21] how to detect relationships among users by parsing the PNL inside probe request messages and resorting to Wigle for geo-localizing APs.…”

Inferring social relationships from technology-level device connections

“…Possibly one of the most concerning privacy-related inferences using technology-device metadata is that proposed in Cunche et al [2] and expanded on later in Cheng et al [25] and Barbera et al [3]. These research articles exploit the fact that wireless-enabled devices, such as smartphones, often use active WiFi probe requests in their search for familiar networks.…”