Detection of Spoofing Attacks in WLAN-Based Positioning Systems Using WiFi Hotspot Tags

Abstract

WLAN-based localization is widely adopted for mobile positioning, which is the prerequisite for location based services and more. However, the existing positioning systems are vulnerable to location spoofing attacks, which may bring major privacy concerns to mobile social network service (MSNS). In this paper, we first show a privacy attack model base on spoofing attack in MSNS, and then propose a novel defense mechanism based on WiFi-hotspot tags (i.e. base-station tags, BS tags). Specially, we utilize the unpredictability and reproducibility of BS tags to authenticate the spatial-temporal property of a geolocation. Furthermore, we introduce the bloom filter to compress parts of real-time hotspots frames, while guaranteeing its high entropy. Also, we design a tag verification algorithm based on the fuzzy extractors, which can well adapt to the high-bit error rates of wireless transmission. Finally, the safety and feasibility of the mechanism are proved by theoretical and experimental analysis.

Keywords

• Social network
• WLAN-based positioning
• location spoofing attack
• WiFi hotspot tags
• fuzzy extractors