STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

Wang, Xinlei; Pande, Amit; Zhu, Jindan; Mohapatra, Prasant

doi:10.1109/tnet.2016.2515119

Cited by 54 publications

(61 citation statements)

References 19 publications

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“…There has been an extensive study on the vulnerabilities and attacks in a proof of location context [1,[4][5][6]16]. Depending on the role, a malicious user has specific purposes which are detailed in the sequel.…”

Section: Malicious Users and Types Of Attacksmentioning

confidence: 99%

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QuietPlace: An Ultrasound-Based Proof of Location Protocol with Strong Identities

Kounas

Voutyras

Palaiokrassas

et al. 2020

ASI

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Location-based services are becoming extremely popular due to the widespread use of smartphones and other mobile and portable devices. These services mainly rely on the sincerity of users, who can spoof the location they report to them. For applications with higher security requirements, the user should be unable to report a location different than the real one. Proof of Location protocols provide a solution to secure localization by validating the device's location with the help of nearby nodes. We propose QuietPlace, a novel protocol that is based on ultrasound and provides strong identities, proving the location of the owner of a device, without exposing though their identity. QuietPlace provides unforgeable proof that is able to resist to various attacks while respecting the users' privacy. It can work regardless of certificate authority and location-based service and is able to support trust schemas that evaluate the participants' behavior. We implement and validate the protocol for Android devices, showing that ultrasound-based profiles offer a better performance in terms of maximum receiving distance than audible profiles, and discuss its strengths and weaknesses, making suggestions about future work.

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Section: Malicious Users and Types Of Attacksmentioning

confidence: 99%

“…In the literature, various techniques are being used, such as distance bounding. Distance bounding consists of a fast bit exchange between prover and witness [4,16]. Those bits are related to cryptographic data that identify the users involved without exposing their identities.…”

Section: Proximity Testmentioning

confidence: 99%

QuietPlace: An Ultrasound-Based Proof of Location Protocol with Strong Identities

Kounas

Voutyras

Palaiokrassas

et al. 2020

ASI

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“…A Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme is proposed by [136]. This scheme is based on a distributed architecture where ad-hoc mobile users generate location proofs for each other.…”

Section: ) Caching Schemes In Mobile Networkmentioning

confidence: 99%

Security and Privacy in Location-Based Services for Vehicular and Mobile Communications: An Overview, Challenges, and Countermeasures

Asuquo

Cruickshank

Morley

et al. 2018

IEEE Internet Things J.

123

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Abstract-Location-based Services (LBS) have gained popularity as a result of the advances in mobile and communication technologies. LBS provide users with relevant information based on their location. In spite of the desirable features provided by LBS, the geographic locations of users are not adequately protected. Location privacy is one of the major challenges in vehicular and mobile networks. In this article, we analyse the security and privacy requirements for LBS in vehicular and mobile networks. Specifically, this paper covers privacy enhancing technologies and cryptographic approaches that provide location privacy in vehicular and mobile networks. The different approaches proposed in literature are compared and open research areas are identified.

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“…(1) Spatio-temporal location. Several works [140,189,191,193,211] have proposed the use of spatio-temporal location of sensing reports to collect trustworthiness evidence. The rationale is that if the report is originated from a location closer to the event being monitored, and has been submitted before a given deadline, then the report and thus the participant is trustworthy.…”

Section: Collection Of Trustworthiness Evidencementioning

confidence: 99%

Quality of Information in Mobile Crowdsensing

Restuccia

Ghosh

Bhattacharjee

et al. 2017

ACM Trans. Sen. Netw.

154

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Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work. F. Restuccia et al.Not only are today's smartphones ubiquitous devices, they are also equipped with a plethora of embedded multi-modal sensors; integrate wireless communication technologies such as 4G/WiFi Internet connectivity, and possess complex processing capabilities. For example, the cameras on smartphones can be used as video and image sensors [29], the microphone can be used as an acoustic sensor [39,154,206], and the embedded global positioning system (GPS) receiver can be used to gather accurate location information, while gyroscopes, accelerometers, and proximity sensors can be used to extract contextual information about the users, such as driving or walking states [75,122]. Further, additional sensors can be easily interfaced with smartphones via Bluetooth or wired connections, such as temperature, air quality, and humidity [69,168].These technological features, combined with the advanced sensing capability of humans, has spurred a significant amount of research from both academia and industry, which together have proposed over the last 10 years a myriad of applications based on the emerging mobile crowdsensing paradigm 1 . Mobile crowdsensing empowers ordinary citizens (or users 2 ) with the capability to actively monitor various phenomena pertaining to themselves (e.g., health, social connections) or their community (e.g., environment). This rich information or inference about themselves or the community may also be sent back to the participating or other concerned users to improve their life experiences, thus influencing their choices. Real-life applications, which can take advantage of both low-level sensor data and high-level user activities, range from real-time traffic monitoring applications, to environmental pollution monitoring, crime monitoring, and social networking, just to name a few. For a survey on mobile crowdsensin...

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STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

Cited by 54 publications

References 19 publications

QuietPlace: An Ultrasound-Based Proof of Location Protocol with Strong Identities

QuietPlace: An Ultrasound-Based Proof of Location Protocol with Strong Identities

Security and Privacy in Location-Based Services for Vehicular and Mobile Communications: An Overview, Challenges, and Countermeasures

Quality of Information in Mobile Crowdsensing

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