Improving wireless privacy with an identifier-free link layer protocol

Greenstein, Ben; McCoy, Damon; Pang, Jong-Shi; Kohno, Tadayoshi; Seshan, Srinivasan; Wetherall, David

doi:10.1145/1378600.1378607

Cited by 89 publications

(49 citation statements)

References 17 publications

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“…In order to address these issues, researchers started to investigate and develop privacy preserving approaches for Wi-Fi, either with minimal modifications to standard 802.11 implementations [11], or as a new protocol version [8]. However, none of these approaches are applied in practice yet.…”

Section: Wi-fimentioning

confidence: 99%

Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures

Schauer¹,

Werner²

2015

ICST Transactions on Ubiquitous Environments

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The rapid deployment of smartphones has led to a wide adoption of wireless communication systems such as Wi-Fi and Bluetooth. Both techniques leak information to the surroundings during operation. This information has been used in literature for estimating pedestrian flows, but the correlation to ground truth has not yet been evaluated. Thus, a reliable deployment in real world scenarios is rather difficult. To fill in this gap, we use ground truth provided by the security check process at a major airport and evaluate the quality of crowd information gathered from Wi-Fi and Bluetooth captures. We analyze estimated pedestrian flows and present three approaches improving the accuracy compared to a naive count of captured MAC addresses. Such counts only showed an impractical Pearson correlation of 0.53 for Bluetooth and 0.61 for Wi-Fi. The presented approaches yield a better correlation and allow for a practical estimation of pedestrian flows.

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Section: Wi-fimentioning

confidence: 99%

Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures

Schauer¹,

Werner²

2015

ICST Transactions on Ubiquitous Environments

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“…[27] identifies several explicit identifiers in 802.11 MAC header that can be used to identify and track users. SlyFi [13] is an 802.11-like link layer protocol that obfuscates all transmitted bits to remove explicit identifiers and increase privacy. [8] provides flexible presence sharing between users with social relationships by broadcasting clique signals.…”

Section: B Private and Verifiable Proximity Computationmentioning

confidence: 99%

Secure friend discovery in mobile social networks

Dong

Dave

Qiu

et al. 2011

2011 Proceedings IEEE INFOCOM

134

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Abstract-Mobile social networks extend social networks in the cyberspace into the real world by allowing mobile users to discover and interact with existing and potential friends who happen to be in their physical vicinity. Despite their promise to enable many exciting applications, serious security and privacy concerns have hindered wide adoption of these networks. To address these concerns, in this paper we develop novel techniques and protocols to compute social proximity between two users to discover potential friends, which is an essential task for mobile social networks. We make three major contributions. First, we identify a range of potential attacks against friend discovery by analyzing real traces. Second, we develop a novel solution for secure proximity estimation, which allows users to identify potential friends by computing social proximity in a privacy-preserving manner. A distinctive feature of our solution is that it provides both privacy and verifiability, which are frequently at odds in secure multiparty computation. Third, we demonstrate the feasibility and effectiveness of our approaches using real implementation on smartphones and show it is efficient in terms of both computation time and power consumption.

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“…To anonymize pseudonyms such as the MAC address, one approach [22] consists in changing the MAC address over time between connections with WiFi access points. Another possibility [20] is to obscure the MAC address and use an identifier-free link layer protocol. However, in peer-to-peer wireless networks, mobile nodes continuously broadcast messages and cannot be anonymized only with respect to WiFi access points.…”

Section: Related Workmentioning

confidence: 99%

On the Optimal Placement of Mix Zones

Freudiger

Shokri

Hubaux

2009

Privacy Enhancing Technologies

143

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Abstract. In mobile wireless networks, third parties can track the location of mobile nodes by monitoring the pseudonyms used for identification. A frequently proposed solution to protect the location privacy of mobile nodes suggests changing pseudonyms in regions called mix zones.In this paper, we propose a novel metric based on the mobility profiles of mobile nodes in order to evaluate the mixing effectiveness of possible mix zone locations. Then, as the location privacy achieved with mix zones depends on their placement in the network, we analyze the optimal placement of mix zones with combinatorial optimization techniques. The proposed algorithm maximizes the achieved location privacy in the system and takes into account the cost induced by mix zones to mobile nodes. By means of simulations, we show that the placement recommended by our algorithm significantly reduces the tracking success of the adversary.

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Improving wireless privacy with an identifier-free link layer protocol

Cited by 89 publications

References 17 publications

Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures

Analyzing Pedestrian Flows Based on Wi-Fi and Bluetooth Captures

Secure friend discovery in mobile social networks

On the Optimal Placement of Mix Zones

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