Leveraging P2P Interactions for Efficient Location Privacy in Database-driven Dynamic Spectrum Access

Abstract Dynamic spectrum access (DSA) is a novel communication paradigm that enables wireless clients to utilize statically allocated radio channels that are currently idle. Specifically, in the database-driven DSA model, clients learn their geographic location through a GPS device and use this location to retrieve a list of available channels from a centralized white-space database. To mitigate the potential privacy threats associated with location-based queries, existing work has proposed the use of private information retrieval (PIR) protocols when querying the database. Nevertheless, PIR protocols are very expensive and may lead to significant costs for highly mobile clients. In this paper, we propose a novel method that allows wireless users to collaborate in a peer-to-peer (P2P) manner, in order to share their cached channel availability information that is obtained from previous queries. To preserve location privacy against other users, we leverage an anonymous veto protocol that anonymizes the exchange of information among a group of users. Our experimental results with a real-life dataset show that our methods reduce the number of PIR queries by 50% to 60%, while incurring low computational and communication costs

SpreadMeNot: A Provably Secure and Privacy-Preserving Contact Tracing Protocol

A plethora of contact tracing apps have been developed and deployed in several countries around the world in the battle against Covid-19. However, people are rightfully concerned about the security and privacy risks of such applications. To this end, the contribution of this work is twofold. First, we present an in-depth analysis of the security and privacy characteristics of the most prominent contact tracing protocols, under both passive and active adversaries. The results of our study indicate that all protocols are vulnerable to a variety of attacks, mainly due to the deterministic nature of the underlying cryptographic protocols. Our second contribution is the design and implementation of SpreadMeNot, a novel contact tracing protocol that can defend against most passive and active attacks, thus providing strong (provable) security and privacy guarantees that are necessary for such a sensitive application. Our detailed analysis, both formal and experimental, shows that SpreadMeNot satisfies security, privacy, and performance requirements, hence being an ideal candidate for building a contact tracing solution that can be adopted by the majority of the general public, as well as to serve as an open-source reference for further developments in the field

Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) constitutes the first method supporting efficient processing of continuous spatial queries over moving objects

Continuous Monitoring of Top-K Queries over Sliding Windows

Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data. The window size can be expressed either in terms of the number of active tuples or time units. We propose a general methodology for top-k monitoring that restricts processing to the sub-domains of the workspace that influence the result of some query. To cope with high stream rates and provide fast answers in an on-line fashion, the data in W reside in main memory. The valid records are indexed by a grid structure, which also maintains book-keeping information. We present two processing techniques: the first one computes the new answer of a query whenever some of the current top-k points expire; the second one partially pre-computes the future changes in the result, achieving better running time at the expense of slightly higher space requirements. We analyze the performance of both algorithms and evaluate their efficiency through extensive experiments. Finally, we extend the proposed framework to other query types and a different data stream model. Copyright 2006 ACM

A Threshold-Based Algorithm for Continuous Monitoring of K Nearest Neighbors

Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naive solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations