Privacy in Location based Systems

2012

In a straight-forward setup, location-based services have many trust assumptions amongst the involved parties. However, some of the parties may be honest while still being interested in learning confidential information, and others can have reasons to cheat where possible. Therefore, system design needs to account for a less than perfect setting. Research in this area is currently focused on reducing the necessary amount of trust required by improving security, privacy and assurance of these systems. This paper provides an introduction to the field.bstract goes here.

— An LBS (location based service) provides services such as finding the nearest location, favourite entertainment areas etc, to the users based on either their residing area or based on the input the give. The services provided by a location based service are typically based on a point of interest database. Therefore retrieval of the data from the database server takes place. The work proposed is a novel protocol for location based queries that has major performance improvements, which is performed based on two stages-firstly, the user determining his/her location privately and secondly, the server protecting its data from unauthorized users for which they have not paid. This protocol enables security for the user's details as well as protects the server's data. The user is protected because the server is unable to determine his/her location. In the same way, the server's data is protected as a malicious user can only decrypt the part of data obtained to the user with the encryption key acquired in the previous phase, that is he/she cannot decrypt the remaining server data that they are not supposed to authorise. In other words, users can never get the data more than what they have paid for. A phase called oblivious transfer phase is present so as to ensure the privacy of the user and a phase called private information retrieval phase is carried out to protect server's data. Keywords— Location based service, Point of Interest database, oblivious transfer phase, Private information retrieval phase.

Nowadays mobile users are using a popular service called Location-Based Services (LBS). LBS is very helpful for a mobile user in finding various Point of Interests (POIs) in their vicinity. To get these services, users must provide their personal information, such as user identity or current location, which severely risks the location privacy of the user. Many researchers are developing schemes that enable a user to use these LBS services anonymously, but these approaches have some limitations (i.e., either the privacy prevention mechanism is weak or the cost of the solution is too much). As such, we are presenting a robust scheme for mobile users that allows them to use LBS anonymously. Our scheme involves a client side application that interacts with an untrusted LBS server to find the nearest POI for a service required by a user. The scheme is not only efficient in its approach, but is also very practical with respect to the computations that are done on a client’s resource constrained device. With our scheme, not only can a client anonymously use LBS without any use of a trusted third party, but also a server’s database is completely secure from the client. We performed experiments by developing and testing an Android-based client side smartphone application to support our argument.

With rapid growth in technology and cost reduction of hardware and storage media, huge amount of data can be acquired and stored. Acquisition and storage of information results in the increase of huge databases. Such databases exceeded the ability of an i ndividual to completely understand and use. The process to analyze such information is more severe in geo - spatial information. In order to analyze and utilize such data repositories to fullest, a few techniques like data mining, expert system, database man agement system, spatial data analysis, machine learning and artificial intelligence etc. have been tried. Nowadays, spatial data mining (SDM) is a well identified domain of data mining. It can be defined as the discovery of interesting, implicit and previo usly unknown knowledge from large spatial data bases .Generally in spatial database the main concern of an individual is with disclosure of their information about personal location history records. An intruder or unauthorized person can acquire informat ion such as frequent locations visits about a particular person by submitting queries by statistical or pattern mining and deriving the required results from extracted records. In this paper, techniques are suggested to protect the location privacy of an individual depending on level of protection they must be provided .

Handbook of Database Security, 2008

Summary. The adoption of location-based services (LBS) brings new privacy threats to users. The user location information revealed in LBS requests may be used by attackers to associate sensitive information of the user with her identity. This contribution focuses on privacy ...

Advanced Location-Based Technologies and Services, 2013

Location-based Services (LBS) have gained popularity as a result of the advances in mobile and communication technologies. LBS provide users with relevant information based on their location. In spite of the desirable features provided by LBS, the geographic locations of users are not adequately protected. Location privacy is one of the major challenges in vehicular and mobile networks. In this article, we analyse the security and privacy requirements for LBS in vehicular and mobile networks. Specifically, this paper covers privacy enhancing technologies and cryptographic approaches that provide location privacy in vehicular and mobile networks. The different approaches proposed in literature are compared and open research areas are identified.

Proc. Interact, 2003

Context -aware computing often involves tracking peoples' location. Many studies and applications highlight the importance of keeping people's location information private. We discuss two types of locationbased services; location-tracking services that are based on other parties tracking the user's location and position-aware services that rely on the device's knowledge of its own location. We present an experimental case study that examines people's concern for location privacy and compare this to the use of location-based services. We find that even though the perceived usefulness of the two different types of services is the same, locationtracking services generate more concern for privacy than posit ion-aware services. We conclude that development emphasis should be given to position-aware services but that location-tracking services have a potential for success if users are given a simple option for turning the location-tracking off.

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.

Dynamic & mobile GIS: investigating change …, 2006