WiFi Secure Access Control System Based on Geofence With the rapid spread and development of the wireless network, secure access control has caught significant attention. The existing WiFi network system access control methods, mainly based on the static password, the MAC address or the usernamepassword, are prone to spoofing attacks, such as malicious users forge the authentication information to access the network and realize the penetration attack of Intranet. In this paper, we propose a new secure access control model based on Geofence to solve the above problems, further strengthening the security of the wireless network system. Our novel solution facilitates 1) providing convenient wireless network service in the trusted zone without authentication 2) isolating cyberattacks outside the security zone 3) monitoring the access smart mobile device real time without affecting usersxe2x80x99 using the wireless network. Furthermore, we present the consideration of the smart mobile device heterogeneity in our model. Through using three different smart mobile devices to experiment, the analytical and experimental results demonstrate that the difference among the devices have a great impact on the device localization and the final access control effect.

Geographic Hints for Passphrase Authentication We propose and study the use of geographic hints to aid memorability of passphrasestyle authentication secrets. Geographic hints are map locations that are selected by the user at the time of passphrase creation, and shown to the user as a hint at the time of passphrase login. We implement the GeoHints system and analyze how geographic hints impact the usability and security of passphrasestyle secrets in a multisession user study (n38). The study involved testing for multiple passphrase interferenceeach participant was asked to recall 4 distinct passphrases. Our study indicates that while geographic hints showed promise for reducing memory interference, GeoHints (as implemented) does not produce a viable authentication system, as the login success rate was 25% 7xe2x80x9311 days after passphrase selection. We analyze the root causes of login errors, finding that most were due to inexact recall of freeform text input. This finding points towards opportunities to improve the system design, and we suggest improvements that we believe will lead to viable systems that employ geographic hints.