Lars Kulik

A formal model of obfuscation and negotiation for location privacy

Obfuscation concerns the practice of deliberately degrading the quality of information in some way, so as to protect the privacy of the individual to whom that information refers. In this paper, we argue that obfuscation is an important technique for protecting an individuals location privacy within a pervasive computing environment. The paper sets out a formal framework within which obfuscated location-based services are defined. This framework provides a computationally efficient mechanism for balancing an individuals need for high-quality information services against that individuals need for location privacy. Negotiation is used to ensure that a location-based service provider receives only the information it needs to know in order to provide a service of satisfactory quality. The results of this work have implications for numerous applications of mobile and location-aware systems, as they provide a new theoretical foundation for addressing the privacy concerns that are acknowledged to be retarding the widespread acceptance and use of location-based services.

Group trip planning queries in spatial databases

In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to a specific category, a starting point S and a destination E, TPQ retrieves the best trip that starts at S, passes through at least one point from each category, and ends at E. For example, a driver traveling from Boston to Providence might want to stop to a gas station, a bank and a post office on his way, and the goal is to provide him with the best possible route (in terms of distance, traffic, road conditions, etc.). The difficulty of this query lies in the existence of multiple choices per category. In this paper, we study fast approximation algorithms for TPQ in a metric space. We provide a number of approximation algorithms with approximation ratios that depend on either the number of categories, the maximum number of points per category or both. Therefore, for different instances of the problem, we can choose the algorithm with the best approximation ratio, since they all run in polynomial time. Furthermore, we use some of the proposed algorithms to derive efficient heuristics for large datasets stored in external memory. Finally, we give an experimental evaluation of the proposed algorithms using both synthetic and real datasets.

Simplest Paths: Automated Route Selection for Navigation

Numerous cognitive studies have indicated that the form and complexity of route instructions may be as important to human navigators as the overall length of route. Most automated navigation systems rely on computing the solution to the shortest path problem, and not the problem of finding the “simplest” path. This paper addresses the issue of finding the “simplest” paths through a network, in terms of the instruction complexity. We propose a “simplest” paths algorithm that has quadratic computation time for a planar graph. An empirical study of the algorithm’s performance, based on an established cognitive model of navigation instruction complexity, revealed that the length of a simplest path was on average only 16% longer than the length of the corresponding shortest path. In return for marginally longer routes, the simplest path algorithm seems to offer considerable advantages over shortest paths in terms of their ease of description and execution. The conclusions indicate several areas for future research: in particular cognitive studies are needed to verify these initial computational results. Potentially, the simplest paths algorithm could be used to replace shortest paths algorithms in any automated system for generating human navigation instructions, including in-car navigation systems, Internet driving direction servers, and other location-based services.

The V*-Diagram: a query-dependent approach to moving KNN queries

The moving k nearest neighbor (MkNN) query finds the k nearest neighbors of a moving query point continuously. The high potential of reducing the query processing cost as well as the large spectrum of associated applications have attracted considerable attention to this query type from the database community. This paper presents an incremental safe-region-based technique for answering MkNN queries, called the V*-Diagram. In general, a safe region is a set of points where the query point can move without changing the query answer. Traditional safe-region approaches compute a safe region based on the data objects but independent of the query location. Our approach exploits the current knowledge of the query point and the search space in addition to the data objects. As a result, the V*-Diagram has much smaller IO and computation costs than existing methods. The experimental results show that the V*-Diagram outperforms the best existing technique by two orders of magnitude.

Safeguarding location privacy in wireless ad-hoc networks

We present a novel algorithm that safeguards the location privacy of users accessing location-based services via mobile devices. Our technique exploits the capability of mobile devices to form wireless ad-hoc networks in order to hide a users identity and position. Local ad-hoc networks enable us to separate an agents request for location information, the query initiator, from the agent that actually requests this service on its behalf, the query requestor. Since a query initiator can select itself or one of the k - 1 agents in its ad-hoc network as a query requestor, the query initiator remains k-anonymous. In addition, the location revealed to the location service provider is a rectangle instead of an exact coordinate. We develop an anonymous selection algorithm that selects a query requestor with near-uniform randomness, which is a key component to ensure anonymity in an ad-hoc network. Our experiments show that a system can ensure a high quality of service and maintain a high degree of privacy in terms of anonymity and obfuscation while accessing location-based services.

Wayfinding choremes-a language for modeling conceptual route knowledge

The emergent interest in ontological and conceptual approaches to modeling route information results from new information technologies as well as from a multidisciplinary interest in spatial cognition. Linguistics investigates verbal route directions; cartography carries out research on route maps and on the information needs of map users; and computer science develops formal representations of routes with the aim to build new wayfinding applications. In concert with geomatics, ontologies of spatial domain knowledge are assembled while sensing technologies for location-aware wayfinding aids are developed simultaneously (e.g. cell phones, GPS-enabled devices or PDAs). These joint multidisciplinary efforts have enhanced cognitive approaches for route directions. In this article, we propose an interdisciplinary approach to modeling route information, the wayfinding choreme theory. Wayfinding choremes are mental conceptualizations of functional wayfinding and route direction elements. With the wayfinding choreme theory, we propose a formal treatment of (mental) conceptual route knowledge that is based on qualitative calculi and refined by behavioral experimental research. This contribution has three parts: First, we introduce the theory of wayfinding choremes. Second, we present term rewriting rules that are grounded in cognitive principles and can tailor route directions to different user requirements. Third, we exemplify various application scenarios for our approach.

Simulation of obfuscation and negotiation for location privacy

Current mobile computing systems can automatically sense and communicate detailed data about a persons location. Location privacy is an urgent research issue because concerns about privacy are seen to be inhibiting the growth of mobile computing. This paper investigates a new technique for safeguarding location privacy, called obfuscation, which protects a persons location privacy by degrading the quality of information about that persons location. Obfuscation is based on spatial imperfection and offers an orthogonal approach to conventional techniques for safeguarding information about a persons location. Imprecision and inaccuracy are two types of imperfection that may be used to achieve obfuscation. A set of simulations are used to empirically evaluate different obfuscation strategies based on imprecision and inaccuracy. The results show that obfuscation can enable high quality of service in concert with high levels of privacy.

Information Dissemination in Mobile Ad-Hoc Geosensor Networks

This paper addresses the issue of how to disseminate relevant information to mobile agents within a geosensor network. Conventional mobile and location-aware systems are founded on a centralized model of information systems, typified by the client-server model used for most location-based services. However, in this paper we argue that a decentralized approach offers several key advantages over a centralized model, including robustness and scalability. We present an environment for simulating information dissemination strategies in mobile ad-hoc geosensor networks. We propose several strategies for scalable, peer-to-peer information exchange, and evaluate their performance with regard to their ability to distribute relevant information to agents and minimize redundancy.

Don't trust anyone: Privacy protection for location-based services

We present a decentralized approach that exploits the capability of mobile devices to form wireless personal ad-hoc networks in order to protect the privacy of users who access location-based services. The novelty of our approach is that users do not need to trust any party such as an intermediary server or peers with their locations and identities. We propose efficient algorithms for users to compute a k-anonymous imprecise location and to randomly select one of her peers with uniform probability who forwards the service request on behalf of the user. Our experimental evaluation shows that using our approach a user can enjoy a high quality of service with a high degree of privacy.

Gesture recognition using RFID technology

We propose a gesture recognition technique based on RFID: cheap and unintrusive passive RFID tags can be easily attached to or interweaved into user clothes, which are then read by RFID antennas. These readings can be used to recognize hand gestures, which enable interaction with applications in an RFID-enabled environment. For instance, it allows people to interact with large displays in public collaboration spaces without the need to carry a dedicated device. We propose the use of multiple hypothesis tracking and the use of subtag count information to track the motion patterns of passive RFID tags. To the best of our knowledge, this work is the first on motion pattern tracking using passive RFID tags. Despite the reading uncertainties inherent in passive RFID technology, our experiments show that the proposed gesture recognition technique has an accuracy of up to 93%.