Client assisted location data acquisition scheme for secure enterprise wireless networks

Pandey, Santosh; Kim, Byungsuk; Anjum, Farooq; Agrawal, F.

doi:10.1109/wcnc.2005.1424675

Cited by 19 publications

(7 citation statements)

References 8 publications

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“…Based on the reception of these beacons, devices compute their positions. In range-based systems [7,18,20,36,39], the localized node (LN) records the signals received from access points, measures their RSS values, converts them into ranges, and estimates its own positions using the measured ranges. In range-free systems, the LN registers which APs are in its reception range and, based on this information, estimates its position.…”

Section: Background: Wlan-based Positioning Systemsmentioning

confidence: 99%

“…In most proposed WLAN-based positioning systems, the APs are controlled by the authority that operates the system. Typically, range-free and range-based WLAN positioning systems achieve a positioning accuracy in the order of meters, and if they rely on location fingerprinting, they can achieve accuracy in the order of tens of centimeters [7,36,39].…”

Section: Background: Wlan-based Positioning Systemsmentioning

confidence: 99%

“…Furthermore, several proposals have been made to improve the security in WLAN-based localization. However, these solutions require the cooperation of the APs [37][38][39]46].…”

Section: Related Workmentioning

confidence: 99%

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Attacks on public WLAN-based positioning systems

Tippenhauer

Rasmussen

Pöpper

et al. 2009

Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services

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In this work, we study the security of public WLAN-based positioning systems. Specifically, we investigate the Skyhook positioning system, available on PCs and used on a number of mobile platforms, including Apple's iPod touch and iPhone. By implementing and analyzing several kinds of attacks, we demonstrate that this system is vulnerable to location spoofing and location database manipulation. In both, the attacker can arbitrarily change the result of the localization at the victim device, by either impersonating remote infrastructure or by tampering with the service database. Our attacks can easily be replicated and we conjecture that-without appropriate countermeasures-public WLAN-based positioning should therefore be used with caution in safety-critical contexts. We further discuss several approaches for securing WLAN-based positioning systems.

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Section: Background: Wlan-based Positioning Systemsmentioning

confidence: 99%

Section: Background: Wlan-based Positioning Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Attacks on public WLAN-based positioning systems

Tippenhauer

Rasmussen

Pöpper

et al. 2009

Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services

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“…Kaemarungsi [14] reported the experimental analysis results on RSS temporal characteristics. [15] proposed a scheme to collect reference measurements from client sniffers periodically. [16] collected reference measurements between APs.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Location Fingerprint Generation Using Extended Signal Propagation Model

Kim¹,

Li²,

Choi³

et al. 2012

Journal of Electrical Engineering and Technology

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-Fingerprinting is a widely used positioning technology for received signal strength (RSS) based wireless local area network (WLAN) positioning system. Though spatial RSS variation is the key factor of the positioning technology, temporal RSS variation needs to be considered for more accuracy. To deal with the spatial and temporal RSS characteristics within a unified framework, this paper proposes an extended signal propagation mode (ESPM) and a fingerprint generation method. The proposed spatiotemporal fingerprint generation method consists of two algorithms running in parallel; Kalman filtering at several measurement-sampling locations and Kriging to generate location fingerprints at dense reference locations. The two different algorithms are connected by the extended signal propagation model which describes the spatial and temporal measurement characteristics in one frame. An experiment demonstrates that the proposed method provides an improved positioning accuracy.

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“…From these, the three closest positions are selected and their position average is used to denote the estimated location for the mobile user. Similarly, in [11], Pandey et al used the second lowest MSE to assist the estimation. They found that if the LMSE and the second lowest mean square error are physically adjacent, then the middle of their locations yields better estimates.…”

Section: Location Searchmentioning

confidence: 99%

Impact of Sniffer Deployment on Indoor Localization

Biaz

Agrawal

2005 International Conference on Collaborative Computing: Networking, Applications and Worksharing

Self Cite

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The demand for location based applications including network intrusion detection has grown tremendously lately. However, location determination of indoor mobile users is challenging because of the complexities of the indoor radio propagation characteristics. A radiofrequency (RF) based indoor localization system, like ARIADNE, typically operates by first constructing a lookup table mapping the radio signal strength at different known locations in the building, and then a mobile user's location at an arbitrary point in the building is determined by measuring the signal strength at the location in question and searching the corresponding location from the above lookup table. Usually, the mobile user's signal strength is measured by three or more sniffers mechanically deployed inside the building. Obviously, the sniffers position configuration and the number of available sniffers greatly affect the localization performance. This paper presents experimental results that explore the impact of the sniffers deployment on the localization based on the ARIADNE system. The results demonstrate that the triangular deployment and extra available sniffers generally generate better localization performance.

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Client assisted location data acquisition scheme for secure enterprise wireless networks

Cited by 19 publications

References 8 publications

Attacks on public WLAN-based positioning systems

Attacks on public WLAN-based positioning systems

Spatiotemporal Location Fingerprint Generation Using Extended Signal Propagation Model

Impact of Sniffer Deployment on Indoor Localization

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