@inproceedings{b9e90db44fd04e56830bde1d23d7eea5,
title = "SPICE: Secure Proximity-based Infrastructure for Close Encounters",
abstract = "We present a crowdsourcing system that extends the capabilities of location-based applications and allows users to connect and exchange information with users in spatial and temporal proximity. We define this incident of spatio-temporal proximity as a close encounter. Typically, location-based application users store their information on a server, and trust the server to provide access only to authorized users, not misuse the data or disclose their location history. Our system, called SPICE, addresses these privacy issues by leveraging Wi-Fi access points to connect users and encrypt their information before it is exchanged, so only users in close encounters have access to the information. We present the design of the system and describe the challenges in implementing the protocol in a real-world application.",
keywords = "Anonymity, Crowdsensing, Encounters, Location, Privacy, Smartphones",
author = "Aarathi Prasad and Xiaohui Liang and David Kotz",
year = "2017",
month = nov,
day = "6",
doi = "10.1145/3139243.3139245",
language = "English",
series = "CrowdSenSys 2017 - Proceedings of the 1st ACM Workshop on Mobile Crowdsensing Systems and Applications, Part of SenSys 2017",
publisher = "Association for Computing Machinery, Inc",
pages = "56--61",
editor = "Rasit Eskicioglu",
booktitle = "CrowdSenSys 2017 - Proceedings of the 1st ACM Workshop on Mobile Crowdsensing Systems and Applications, Part of SenSys 2017",
note = "1st ACM Workshop on Mobile Crowdsensing Systems and Applications, CrowdSenSys 2017 ; Conference date: 05-11-2017",
}