ENHANCING PRIVACY FOR USERS USING LOCATION BASED SERVICES

International Journal of Engineering & Technology, 2017

This paper presents a solution to one of the situation-based totally question problems. This downside is printed as follows: (i) a user desires to question a data of area records, referred to as factors Of interest (POI), and doesn't want to reveal his/her vicinity to the server way to privacy concerns; (ii) the proprietor of the state of affairs data, that is, the place server, would not wish to effortlessly distribute its statistics to any or all users. The scenario server needs to personal a few control over its data, since the data is its fine. A location based question resolution that employs 2 protocols that allows a person to privately verify and acquire vicinity statistics. The primary step is for a consumer to in private verify his/her region victimization oblivious switch on a public grid. Oblivious switch accustomed supply the goods a more secure resolution for every parties. the second one step involves a personal information retrieval interplay that retrieves the re...

Jomo Kenyatta University of Agriculture and Technology, 2016

This paper presents a framework for enhancing privacy in Location Based Services using K-anonymity model. Users of location based services have to reveal their location information in order to use these services; however this has threatened the user privacy. K-anonymity approach has been studied extensively in various forms. However, it is only effective when the user location is fixed. When a user moves and continuously sends their location information, the location service provider can approximate user trajectory which poses a threat to the trajectory privacy of the user. This framework will ensure that user privacy is enhanced for both snapshot and continuous queries. The efficiency and effectiveness of the proposed framework was evaluated, the results indicate that the proposed framework has high success rate and good run time performance.

2015

Location-Based Service (LBS) becomes increasingly popular with the dramatic growth of smartphones and social network services (SNS), and its context-rich functionalities attract considerable users. Many LBS providers use users' location information to offer them convenience and useful functions. However, the LBS could greatly breach personal privacy because location itself contains much information. Hence, preserving location privacy while achieving utility from it is still a challenging question now. This paper tackles this non-trivial challenge by designing a suite of novel fine-grained Privacy-preserving Location Query Protocol (PLQP). Our protocol allows different levels of location query on encrypted location information for different users, and it is efficient enough to be applied in mobile platforms.

The services offers by LBS (Location based service) are characteristically based on a point of interest record. By recover the Points Of Interest (POIs) from the database server, the user can get reply to a variety of location based queries, which comprise but are not incomplete to determine the nearest ATM machine, gas station, hospital, or police station. Amongst numerous demanding blockades to the extensive operation of such submission, solitude declaration is a main question. The Location Server (LS), which proffer some LBS, expend its possessions to accumulate information about a variety of interesting POIs. Consequently, it is normal that the LS would not unveil any information devoid of amount. Therefore the LBS have to make certain that LS's data is not way in by any unofficial consumer. Unfortunately, existing privacy-preserving techniques for LBS have several limitations, such as requiring a fully-trusted third party, offering limited privacy guarantees and incurring h...

ACM SIGKDD Explorations Newsletter, 2010

The offering of anonymity in relational databases has attracted a great deal of attention in the database community during the last decade . Among the different solution approaches that have been proposed to tackle this problem, K-anonymity has received increased attention and has been extensively studied in various forms. New forms of data that come into existence, like location data capturing user movement, pave the way for the offering of cutting edge services such as the prevailing Location Based Services (LBSs). Given that these services assume an in-depth knowledge of the mobile users' whereabouts it is certain that the assumed knowledge may breach the privacy of the users. Thus, concrete approaches are necessary to preserve the anonymity of the mobile users when requesting LBSs. In this work, we survey recent advancements for the offering of K-anonymity in LBSs. Most of the approaches that have been proposed heavily depend on a trusted server component -that acts as an intermediate between the end user and the service provider -to preserve the anonymity of the former entity. Existing approaches are partitioned in three categories: (a) historical K-anonymity, (b) location K-anonymity, and (c) trajectory K-anonymity. In each of these categories we present some of the most prevalent methodologies that have been proposed and highlight their operation.

2010 Eleventh International Conference on Mobile Data Management, 2010

The emerging location-detection devices together with ubiquitous connectivity have enabled a large variety of locationbased services (LBS). Unfortunately, LBS may threaten the users' privacy. K-anonymity cloaking the user location to Kanonymizing spatial region (K-ASR) has been extensively studied to protect privacy in LBS. Traditional K-anonymity method needs complex query processing algorithms at the server side. SpaceTwist [8] rectifies the above shortcoming of traditional Kanonymity since it only requires incremental nearest neighbor (INN) queries processing techniques at the server side. However, SpaceTwist may fail since it cannot guarantee K-anonymity. In this paper, our proposed framework, called KAWCR (Kanonymity Without Cloaked Region), rectifies the shortcomings and retains the advantages of the above two techniques. KAWCR only needs the server to process INN queries and can guarantee that the users issuing the query is indistinguishable from at least K-1 other users. We formulate the communication costs of KAWCR, traditional K-anonymity and SpaceTwist under the assumptions that POIs and users are uniformly distributed. We also did extensive experiments to compare KAWCR with traditional K-anonymity and SpaceTwist in terms of communication costs. The experimental results show that the communication cost of KAWCR for kNN queries is lower than that of both traditional K-anonymity and SpaceTwist.

Computer Networks, 2012

We address issues related to privacy protection in location-based services (LBSs). Most existing privacy-preserving LBS techniques either require a trusted third-party (anonymizer) or use cryptographic protocols that are computationally and communicationally expensive. Our design of privacy-preserving techniques is principled on not requiring a trusted third-party while being highly efficient in terms of time and space complexities. The problem has two interesting and challenging characteristics: First, the degree of privacy protection and LBS accuracy depends on the context, such as population and road density, around a user's location. Second, an adversary may violate a user's location privacy in two ways: (i) based on the user's location information contained in the LBS query payload and (ii) by inferring a user's geographical location based on the device's IP address. To address these challenges, we introduce CAP, a context-aware privacy-preserving LBS system with integrated protection for both data privacy and communication anonymity. We have implemented CAP and integrated it with Google Maps, a popular LBS system. Theoretical analysis and experimental results validate CAP's effectiveness on privacy protection, LBS accuracy, and communication QoS (Quality-of-Service).

Lecture Notes in Computer Science, 2014

Finding a convenient meeting point for a group is a common problem. For example, a group of users may want to meet at a restaurant that minimizes the group's total travel distance. Such queries are called Group Nearest Neighbor (GNN) queries. Up to now, users have had to rely on an external party, typically a location service provider (LSP), for computing an optimal meeting point. This implies that users have to trust the LSP with their private locations. Existing techniques for private GNN queries either cannot resist sophisticated attacks or are computationally too expensive to be implemented on the popular platform of mobile phones. This paper proposes an algorithm to efficiently process private GNN queries. To achieve high efficiency we propose an approach that approximates a GNN with a high accuracy and is robust to attacks. Unlike methods based on obfuscation, our method does not require a user to provide an imprecise location and is in fact location oblivious. Our approach is based on a distributed secure sum protocol which requires only light weight computation. Our experimental results show that we provide a readily deployable solution for real life applications which can also be deployed for other geo-spatial queries and applications.

2011

Users of location-based services (LBSs) may have serious privacy concerns when using these technologies since their location can be utilized by adversaries to infer privacy-sensitive information about them. In this work, we analyze the mainstream anonymity solutions proposed for LBSs based on k-anonymity, and point out that these do not follow the safe assumptions as per the original definition of k-anonymity. We propose an alternative LBS anonymity property, LBS (k,T)-anonymity, that ensures anonymity of a user's query against an attacker who knows about the issuance of the user query within a time window. We evaluate the vulnerability of the approaches in the literature to this type of attack that we believe is very basic and important, and assess the performance of our proposed algorithm for achieving LBS (k,T)-anonymity in terms of providing optimal solution.

2011 Proceedings IEEE INFOCOM, 2011

Location-based services (LBS) have become an immensely valuable source of real-time information and guidance. Nonetheless, the potential abuse of users' sensitive personal data by an LBS server is evolving into a serious concern. Privacy concerns in LBS exist on two fronts: location privacy and query privacy. In this paper we investigate issues related to query privacy. In particular, we aim to prevent the LBS server from correlating the service attribute, e.g., bar/tavern, in the query to the user's real-world identity. Location obfuscation using spatial generalization aided by anonymization of LBS queries is a conventional means to this end. However, effectiveness of this technique would abate in continuous LBS scenarios, i.e., where users are moving and recurrently requesting for LBS. In this paper, we present a novel query-perturbation-based scheme that protects query privacy in continuous LBS even when useridentities are revealed. Unlike most exiting works, our scheme does not require the presence of a trusted third party.