Enhancing Location Privacy in Wireless LAN Through Disposable Interface Identifiers: A Quantitative Analysis

By Marco Gruteser, Dirk Grunwald. Wireless Mobile Applications and Services on WLAN Hotspots, 2003

311 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/4f0841b5c4a1afbd67c9cf953a3ac27597694108

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In Artificial Intelligence

In Computer Networks and Communications

Citations in the corpus

Engineering Privacy (2009, background): “Another approach involves using clients that frequently change their network identifiers to reduce the ability of service providers to track a client over time [88].”
Over-exposed?: privacy patterns and considerations in online and mobile photo sharing (2007, background): “The privacy issues with mobile and networked devices have been explored for networked desktops [6,10], wireless devices [11,17], mobile phones [3] as well as sensor networks [12].”
CARAVAN: Providing Location Privacy for VANET (2005, background): “These numbers are approximated from [19], where 24-hour traffic volume estimates are provided based on real traffic data.”
Anonysense: privacy-aware people-centric sensing (2008, methodology): “We assume the MN changes its MAC and IP addresses using one of the standard mechanisms [16, 20] so that an MN’s report and task actions may not be linked.”
Supporting anonymous location queries in mobile environments with privacygrid (2008, background): “The simulator extracts the road network based on three types of roads - expressway, arterial and collector roads.”
AMOEBA: Robust Location Privacy Scheme for VANET (2007, background): “[16], [41] have worked extensively on protecting location privacy in WLAN, and utilize vehicular traffic data for evaluating their proposed solutions.”
Enhancing wireless location privacy using silent period (2005, unknown): “a client’s interface identifier [7], [8].”
SDDR: Light-Weight, Secure Mobile Encounters (2014, background): “This level of energy consumption is four orders of magnitude more efficient than prior cryptographic protocols with proven security, and one order of magnitude more efficient than prior (unproven) protocols designed specifically for energy-constrained devices.”
Mix-Zones for Location Privacy in Vehicular Networks (2007, background): “Gruteser and Grünwald propose in [12] a network-centric solution in that direction.”
Detecting identity-based attacks in wireless networks using signalprints (2006, background): “have proposed the use of temporary interface identifiers to improve privacy in WLANs: clients change their MAC addresses whenever they associate with an access point, reducing the chances of being tracked [10].”
Preserving privacy in gps traces via uncertainty-aware path cloaking (2007, background): “The usage of silent periods [25, 39, 36, 29], periods of no communication, was proposed for wireless networks to reduce exposure to tracking.”
Security and Privacy Vulnerabilities of In-Car Wireless Networks: A Tire Pressure Monitoring System Case Study (2010, background): “First, wireless devices are known to present tracking risks through explicit identi(cid:2)ers in protocols [20] or identi(cid:2)able patterns in waveforms [10].”