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Traditionally, pollution measurements are performed using expensive equipment at fixed locations or dedicated mobile equipment laboratories. This is a coarse-grained and expensive approach where the pollution measurements are few and far in-between. In this paper, we present a vehicular-based mobile approach for measuring fine-grained air quality in(More)
To support privacy-aware management of data in social spaces, the user personal data needs to be stored at each user device, and shared only with a trusted subset of other users. To date, social spaces only have fairly limited access control capabilities, that do not protect the possibly sensitive data of the users. In this demonstration, we showcase our(More)
Deterministic Approach • Goal: verify each tuple has been assigned to the nearest centroid • Brute-force approach: for each tuple, compute its distance to all cluster centroids. • Our approach: for each tuple, compute its distance to all of its Voronoi centroid neighbors. • Service provider (server)-provides storage and computational power as the service. •(More)
a r t i c l e i n f o a b s t r a c t Data publishing has generated much concern on individual privacy. Recent work has shown that different background knowledge can bring various threats to the privacy of published data. In this paper, we study the privacy threat from the full functional dependency (FFD) that is used as part of adversary knowledge. We show(More)
Spurred by developments such as cloud computing, there has been considerable recent interest in the data-mining-as-a-service paradigm. Users lacking in expertise or computational resources can outsource their data and mining needs to a third-party service provider (server). Out-sourcing, however, raises issues about result integrity: how can the data owner(More)
We study the privacy threat by publishing data that contains full functional dependencies (FFDs). We show that the cross-attribute correlations by FFDs can bring potential vulnerability to privacy. Unfortunately, none of the existing anonymization principles can effectively prevent against the FFD-based privacy attack. In this paper, we formalize the(More)
The intent of peer data management systems (PDMS) is to share as much data as possible. However, in many applications leverag-ing sensitive data, users demand adequate mechanisms to restrict the access to authorized parties. In this paper, we study a distributed access control model, where data items are stored, queried and authenticated in a totally(More)
The data-mining-as-a-service (DMaS) paradigm enables the data owner (client) that lacks expertise or computational resources to outsource its mining tasks to a third-party service provider (server). Outsourcing, however, raises a serious security issue: how can the client of weak computational power verify that the server returned correct mining result? In(More)
Navigators based on real-time traffic achieve suboptimal results since, in face of congestion, they greedily shift drivers to currently light-traffic roads and cause new traffic jams. This paper presents Themis, a participatory system navigating drivers in a balanced way. By analyzing time-stamped position reports and route decisions collected from the(More)