Towards Region Queries with Strong Location Privacy in Mobile Network

With the interaction of geographic data and social data, the inference attack has been mounting up, calling for new technologies for privacy protection. Although there are many tangible contributions of spatial-temporal cloaking technologies, traditional technologies are not enough to resist privacy intrusion. Malicious attackers still steal user-sensitive information by analyzing the relationship between location and query semantics. Reacting to many interesting issues, oblivious transfer (OT) protocols are introduced to guarantee location privacy. To our knowledge, OT is a cryptographic primitive between two parties and can be used as a building block for any arbitrary multiparty computation protocol. Armed with previous privacy-preserving technologies, for example, OT, in this work, we first develop a novel region queries framework that can provide robust privacy for location-dependent queries. We then design an OT-assist privacy-aware protocol (or OTPA) for location-based service with rigorous security analysis. In short, the common query of the client in our solution can be divided into two parts, the region query R q and the content query C q , to achieve location k -anonymity, location m -diversity, and query r -diversity, which ensure the privacy of two parties (i.e., client and server). Lastly, we instantiate our OTPA protocol, and experiments show that the proposed OTPA protocol is reasonable and effective.

Research on the Ranked Searchable Encryption Scheme Based on an Access Tree in IoTs

With the continuous development of the Internet of things (IoTs), data security and privacy protection in the IoTs are becoming increasingly important. Aiming at the hugeness, redundancy, and heterogeneity of data in the IoTs, this paper proposes a ranked searchable encryption scheme based on an access tree. First, this solution introduces parameters such as the word position and word span into the calculation of the relevance score of keywords to build a more accurate document index. Secondly, this solution builds a semantic relationship graph based on mutual information to expand the query semantics, effectively improving the accuracy and recall rate during retrieval. Thirdly, the solution uses an access tree control structure to control user authority and realizes fine-grained access management to data by data owners in the IoTs. Finally, the safety analysis of this scheme and the efficiency comparison with other existing schemes are given.

Geo-Social Top-k and Skyline Keyword Queries on Road Networks

The rapid growth of GPS-enabled mobile devices has popularized many location-based applications. Spatial keyword search which finds objects of interest by considering both spatial locations and textual descriptions has become very useful in these applications. The recent integration of social data with spatial keyword search opens a new service horizon for users. Few previous studies have proposed methods to combine spatial keyword queries with social data in Euclidean space. However, most real-world applications constrain the distance between query location and data objects by a road network, where distance between two points is defined by the shortest connecting path. This paper proposes geo-social top-k keyword queries and geo-social skyline keyword queries on road networks. Both queries enrich traditional spatial keyword query semantics by incorporating social relevance component. We formalize the proposed query types and appropriate indexing frameworks and algorithms to efficiently process them. The effectiveness and efficiency of the proposed approaches are evaluated using real datasets.

A Schema-Based Approach to Enable Data Integration on the Fly

On-the-fly data integration, i.e. at query time, happens mostly in tightly coupled, homogeneous environments where the partitioning of the data can be controlled or is known in advance. During the process of data fusion, the information is homogenized and data inconsistencies are hidden from the application. Beyond this, we propose in this paper the Nexus metadata model and a processing approach that support on-the-fly data integration in a loosely coupled federation of autonomous data providers, thereby advancing the status quo in terms of flexibility and expressive power. It is able to represent data and schema inconsistencies like multi-valued attributes and multi-typed objects. In an open environment, this best suites the application needs where the data processing infrastructure is not able to decide which attribute value is correct. The Nexus metadata model provides the foundation for integration schemata that are specific to a given application domain. The corresponding processing model provides four complementary query semantics in order to account for the subtleties of multi-valued and missing attributes. In this paper we show that this query semantics is sound, easy to implement, and it builds upon existing query processing techniques. Thus the Nexus metadata model provides a unique level of flexibility for on-the-fly data integration.

A Fast Approach for SLCA in Keyword Query over XML Document

Query evaluation and query semantics in the XML keyword query, has an important role, which directly affect the performance of XML query. This paper proposes a fast approach for SLCA in keyword query over XML document,which can judge the information of relevant nodes by means of self-definition to document nods type.This method can solve the problems of no significance of node information query results of the XKSearch algorithm, and compared with XSeek algorithm, it has high efficiency in the query time consumed for the returned results. Experiments show that this method is more efficient in query time and quality of keywords query.