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Location Based Services in the world of mobile devices has been used widely in all sectors and in various applications. It allows one to track the location, track services and also perfom other location based operations. Although it's uses are very significant, the information related to location has opened up opportunities for adversary to misuse the mobile clients. This paper addresses one such...
Data-driven business processes are gaining popularity among enterprises now-a-days. In many situations, multiple parties would share data towards a common goal if it were possible to simultaneously protect the privacy of the individuals and organizations described in the data. Existing solutions for multi-party analytics require parties to transfer their raw data to a trusted mediator, who then performs...
systems for providing data privacy, there is no general methodology for determining the extent to which these techniques, tools and systems reduce practical privacy risks. We need a comprehensive framework where the privacy and utility of multiple privacy-preserving techniques could be measured. This vision paper provides directions for designing such a framework.
The paper introduces a research agenda for security and privacy in big data. The paper discusses research challenges and directions concerning data confidentiality, privacy, and trustworthiness in the context of big data. Key research issues discussed in the paper include how to reconcile security with privacy, the notion of data ownership, and how to enforce access control in big data stores.
This paper summarizes opportunities and challenges concerning how we can achieve security while still ensuring privacy. It identifies research directions and includes a number of questions that have been debated by the panel.
In mobile communication, spatial queries pose a serious threat to user location privacy because the location of a query may reveal sensitive information about the mobile user. In this paper, we study k nearest neighbor (kNN) queries where the mobile user queries the location-based service (LBS) provider about k nearest points of interest (POIs) on the basis of his current location. We propose a solution...
This paper summarizes opportunities and challenges of big data. It identifies important research directions and includes a number of questions that have been debated by the panel.
This paper complements our privacy preserving distributed OLAP framework proposed in [8] by introducing four major theoretical properties that extend models and algorithms presented in [8], where the experimental validation of the framework has also been reported. Particularly, the framework [8] makes use of the CUR matrix decomposition technique [12] as the elementary component for computing privacy...
Current approaches for enforcing fine-grained access control and confidentiality to sensitive data hosted in the cloud are based on selectively encrypting the data before uploading it to the cloud. In such an approach, organizations have to enforce authorization policies through encryption. They thus incur high communication and computation cost to manage keys and encryptions whenever user credentials...
The secure sum protocol is a well-known protocol for computing the sum of private inputs from distributed entities such that the inputs remain private. In this paper we present protocols for computing reputation in a privacy preserving manner that are inspired by the secure sum protocol. We provide a protocol that is secure under the semi-honest adversarial model as well as one that is secure under...
We propose a novel scheme for selective distribution of content, encoded as documents, that preserves the privacy of the users to whom the documents are delivered and is based on an efficient and novel group key management scheme. Our document broadcasting approach is based on access control policies specifying which users can access which documents, or subdocuments. Based on such policies, a broadcast...
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